From recommendations to action

For years, AI has been stuck in advisor mode. It surfaces insights, generates recommendations, and flags anomalies. Then it hands the baton back to humans to actually do something about it. That created a new problem: death by dashboard. More data, more alerts, more decisions for already-stretched teams to make.

Our agentic solutions break that cycle. They don’t just recommend; they predict, decide, and act autonomously in complex real-world environments. They handle the execution at scale while you focus on what matters most.

This is the future of AI in business: not software that requires constant human intervention, but intelligent agents that amplify what your teams can accomplish.

Amplifying output through the AI formula

I recently wrote about a simple but powerful formula that sits at the heart of business performance:

Output = Decision Accuracy × Resource Performance

These agentic solutions are designed to optimize every part of that equation simultaneously.

Decision accuracy

Agentic AI doesn’t rely on intuition or historical rules of thumb. It continuously learns from real-world outcomes, simulates thousands of scenarios, and makes decisions that balance competing objectives — like revenue, margin, inventory, and service levels — with precision that humans simply can’t match at scale.

Activity rate

What once took days of merchandiser time or supply chain analysis now happens continuously and automatically. And it’s not about replacing people — it’s about freeing them from repetitive work to focus on strategic decisions that rely on human judgment.

Resource performance

These agents don’t just improve individual decisions, but drive performance enhancements across your entire operation. Moving products through your network, rebalancing inventory, adjusting prices in real-time based on market conditions. Every resource works harder, is deployed more intelligently, and responds faster to change.

Why this matters now

We’re living in an era of relentless complexity. Market volatility, supply chain disruptions, and constantly shifting customer demand means the pressure on businesses to adapt quickly has never been greater.

Traditional approaches can’t keep up, and dashboards alone can’t solve this. Even the smartest and fastest teams can’t manually optimize thousands of interconnected decisions quickly enough.

That’s exactly what agentic AI was built for. Not to replace human expertise, but to amplify it. To handle the complexity at scale while your teams focus on innovation, strategy, and the decisions where human judgment is irreplaceable.

George Foster-Jones from Speedy Hire captured it perfectly: “Our vision is to have specialized AIs working alongside our teams to optimise every price we set. This ensures our customers always get the best possible offer and service.”

‘Alongside’ is the key word here. This is all about augmentation, not replacement — giving your team superhuman capabilities.

A new era of AI in practice

I’ve spent over a decade deploying AI in real-world business environments, and I can tell you this: the technology has finally caught up to the vision. Large language models have unlocked capabilities that simply weren’t possible before. Agents that can reason, adapt, and act autonomously in ways that create measurable, meaningful business outcomes.

This is AI in practice. Not experiments or pilots, but production-ready solutions already driving performance for some of the world’s most demanding organizations.

And we’re just getting started.

The future of AI isn’t about giving you more data to analyze or more decisions to make. It’s about intelligent agents that multiply what your teams can accomplish — making your business faster, sharper, and more resilient in the face of whatever comes next.

Welcome to the agentic era.

Your performance is your decisions

Here’s a simple truth for any executive or business leader: your performance directly correlates to your company’s output. Whether you’re running a team, a division, or the entire organization. And, business performance is the sum total of all decisions made; from daily operational calls to strategic investments taken years ago.

That creates an interesting challenge. Leaders are responsible for the quality of decision making across their organizations, yet are often far removed from where many of those decisions happen. This distance is why intuition and experience matter so much in leadership roles. But experience doesn’t automatically guarantee accuracy — and accuracy alone doesn’t always equal performance.

The business performance equation

I believe, that at the heart of business performance, there’s a simple but powerful formula:

Output = Decision Accuracy × Resource Performance

In other words, the output (or performance) of our business is governed entirely by the accuracy of our decisions multiplied by the performance of all of our resources. This is an important and powerful framework; one that I believe should sit at the core of how we think about leadership and performance.

Why? Think about it like this. A brilliant decision with zero resources behind it won’t deliver anything. Equally, abundant resources coupled with poor decisions won’t get you very far either. Performance is the result of how decisions and resources interact.

What does resource performance mean?

Resources are not just people. They are all the resources available to your business, and they should increase over time as your equity grows. Resources fall into 2 groups; performance combines:

• Fixed resources, such as your IP, product, infrastructure, factories, and brand
• Variable resources such as your people, cash, inventories, and processes

But those resources might just sit there doing nothing, right? They must be deployed and this deployment I call an activity rate. This is the speed and frequency with which those resources are put to work.

In other words, resource performance is about both the mix of what you have and how effectively you deploy it.

The final business performance equation

This means that company output isn’t just about isolated good calls at the top. It’s the sum total of everyone’s decisions, multiplied by how well your resources are performing, and how fast things get done. And as business leaders our job can simply be described as making the best possible decisions, with the optimal resource mix as much as we can, as often as possible.

Optimizing this equation cuts to the heart of leadership performance. And in the AI era, it provides a clear and unique lens for assessing how technology can make the biggest difference.

AI can optimize every part of the equation

If output equals decision accuracy multiplied by resource performance, then the role of AI becomes clear: it’s a technology that can be used to optimize each part of that equation.

When evaluating AI opportunities, the key question to ask is simple:

Does this initiative improve accuracy, resource performance, or activity rate — and therefore output?

AI can be particularly impactful across these three levers:

Improving decision accuracy

AI helps leaders move beyond intuition. For example, AI-powered pricing optimization can simulate thousands of markdown scenarios, letting you target specific sell-through, margin, or revenue goals with confidence instead of relying on gut instinct.

Boosting activity rate

Automation speeds up decision cycles. What once took days of manual analysis can now be done in minutes. That means you can make more decisions across the entire range of your business, not just focus on the outliers (your bestsellers or worst performers).

Optimizing resource performance

AI continuously rebalances how resources are deployed — adjusting inventory, reallocating cash, or refining staffing levels — based on real-time conditions instead of static, periodic reviews.

The beauty of this framework lies in its simplicity. No matter how complex the AI initiative, you can always evaluate it by asking: Which part of the equation does this optimize?

If it doesn’t improve accuracy, resource performance, or activity rate, then it won’t meaningfully improve business output.

The bottom line

Your role as a business leader is to maximize output by making the best possible decisions, with the optimal mix of resources, as often and effectively as possible. And AI doesn’t change that responsibility, but amplifies it.

The leaders and organizations that thrive in the AI era won’t just be the ones who adopt the flashiest or most advanced tools. They’ll be the ones who use AI deliberately and strategically to sharpen decision accuracy, accelerate activity, and get the most out of their current resources.

That’s the real test for AI in business — it’s not about how advanced it looks or sounds, but whether it makes the equation work harder.

Why UiPath, and why now?

As automation and agentic AI converge, we’re entering a new era of enterprise AI. The ability to seamlessly integrate decision intelligence with automation presents an unprecedented opportunity to redefine how businesses operate.

UiPath is the global leader in enterprise automation, and their mission aligns perfectly with ours. With their reach, expertise and commitment to AI-driven innovation, we can accelerate our vision — putting decision-making AI in the hands of even more businesses, at a scale we could never have achieved alone.

By joining forces, we will:

Supercharge AI-powered automation: Combining Peak’s decision intelligence with UiPath’s industry-leading automation capabilities will create a powerful, end-to-end AI + automation solution for enterprises.
Expand our reach and impact: UiPath’s global presence and enterprise customer base will help bring Peak’s AI technology to thousands of organizations worldwide.
Innovate faster than ever: With UiPath’s resources and AI expertise, we can push the boundaries of what’s possible, delivering more advanced, integrated AI solutions to our customers.

What this means for our customers and team

For our customers, this is an exciting milestone. Our core technology, team and vision remain unchanged — only now, we have the backing of one the most respected AI and automation companies in the world. Together, we will deliver even greater value, ensuring that businesses can not only make smarter decisions with AI but also act on them seamlessly through automation.

For our team, this marks a huge opportunity for growth, collaboration and impact. UiPath’s culture of innovation and excellence makes it the perfect environment for us to continue pushing the boundaries of decision intelligence and AI-driven automation.

A proud moment for Manchester and Jaipur

One of the things we’re most proud of at Peak is that we’ve built this company outside of the traditional enterprise software hubs, proving that world-class AI and enterprise technology can thrive in places like Manchester and Jaipur. From day one, we’ve been committed to fostering innovation, creating jobs and building a global AI leader from these incredible cities. 

This milestone is not just a success for Peak — it’s a testament to the talent, ambition and growing tech ecosystems in both Manchester and Jaipur. Joining UiPath means even greater opportunities for our teams, our communities and the next generation of AI and automation pioneers in these regions. We’re excited to continue championing Manchester and Jaipur as global hubs for AI excellence and enterprise innovation.

Looking ahead

This is just the beginning. Over the coming months, we’ll be working closely with the UiPath team to explore new possibilities, integrate our technologies and deliver even more powerful AI solutions for enterprises worldwide.

I want to personally thank everyone who has been part of our journey so far — our customers, our team, our partners and our investors. Your support, trust and belief in our vision have made this possible, and we can’t wait to show you what’s next.

Stay tuned for more updates, and as always, feel free to reach out with any questions. The future of AI and automation is here, and we’re just getting started.

Richard, David & Atul
Co-Founders, Peak

The dreaded digital transformation

We mostly see new technology adoption as part of larger digital transformation programs. These extensive programs leave no stone, or morsel of data, unturned. Although comprehensive in theory, this approach is lengthy and expensive, as entire teams are created to lead the change, systems are ripped and replaced and employees are retrained.

Trying to coordinate significant change across an entire organization is difficult, and rarely successful. Oftentimes, it’s seen as a task for IT teams but technology is only an enabler to digital transformation. A strong vision, an accompanying business strategy and a committed leadership team with a desire to reorganize business operations around technology are the core requirements for success.

Whether changing a procurement system, an HR tool or both, digital transformation requires business-wide collaboration. Yet when digital transformation programs don’t go to plan, the blame often falls on technology for failing to deliver value. So, let’s look at what’s really going on.

Technology: a team sport

When things go awry, scope creep is the primary culprit. Even if the initial objectives and requirements of a digital transformation program are adequately defined, it only takes one hiccup for it to quickly spiral out of control. The result of scope creep is delayed rollout, delayed value and increased costs.

Not only that, a long-term program comes with a long-term vision. It’s an appealing vision, a blissful state where employees and technology work hand in hand, but getting initial buy-in from employees and then maintaining momentum for years is a mammoth challenge for any leadership, communications or project team.

When motivation decreases because of scope creep or general reluctance to change, encouraging employees to adapt to new tools or ways of working gets even harder. If only 0.01% of the world will complete a marathon, why, when it comes to digital transformation, are we expecting 100% of businesses to complete one?

And then there’s technology. The technology itself is usually very reliable. Give it some data and you’ll get an output—it works. What isn’t as reliable is its ability to deliver the value you’re looking for and get your team using it, consistently. I’d argue that it comes back to your vision and business strategy: What are you aiming to achieve, what is the most suitable technology to help you do that and what input does it need?

So, despite the performance of technology being only one of several potential causes of business transformation strife, it takes the brunt of the blame. It’s this risk — or perceived risk — of troublesome technology, compounded by economic uncertainty, which places business leaders who know they need to evolve in a tricky position.

Doing nothing isn’t an option, but in uncertain times, the margin for error is unforgiving.

Unlocking low-risk innovation

The arrival of AI in the mainstream is the biggest change for businesses since the dawn of mainframe computing. Even though there’s no shortage of solutions to choose from, many leaders simply don’t have the budget to invest in technology that risks ending up unused, collecting digital dust. In the next few years, businesses using the technology versus those who aren’t will become apparent.

But AI doesn’t have to be high-risk. As the technology matures, performance guarantees are becoming more prominent, providing budget holders with the much-needed assurance that their AI investment will return value. For AI skeptics within teams, they crucially increase confidence in the performance of the technology.

Whether it’s inflation, economic volatility or your own digital transformation project that’s getting you down, unlocking innovation requires confidence in your technology investments. Once you have that, there’s no limit to your AI success.

This article was originally written and published for Forbes Business Council on 28 May 2024.

Ease and efficiency aren’t the only reasons to integrate AI with your existing tech stack

The concept of integrating your business systems is nothing new; don’t use an AI platform that doesn’t talk to your existing tech stack — it’s difficult, costly and often ineffective. But now, we’re starting to see the value of connecting existing systems and software with a business’ chosen AI provider, and that’s pretty exciting.

SAP, for example, is a core part of tech stacks across industries, helping organizations to manage and automate their core business processes, from human resources to customer relationships. The SAP Integration Suite enables users to directly leverage AI outputs from partners (like Peak!) into their existing ecosystem, reducing manual touch points across their processes.

Another advancement is the combination of AI and automation, which has unlocked a whole new level of productivity. UiPath is a business automation platform that helps organizations to automate repetitive tasks and streamline end-to-end processes, such as procure–to–pay, using robotic process automation (RPA) and AI-driven automation capabilities including Comms Mining and Document Understanding.

Using AI to scour terabytes of enterprise data and make intelligent decisions, UiPath and its partners reveal additional value for its customers to further adapt and optimize their processes. For example, joint Peak and UiPath customer, Heidelberg Materials, has seen an increase in margin and conversion rate, as well as estimating thousands of hours saved annually.

Additionally, with Snowflake, a cloud data platform that allows businesses to store, process, and analyze data, businesses can rely on their data as a single source of truth. In turn, this accelerates subsequent implementation of AI solutions and decreases the time it takes for a business to see a return on investment. Peak’s Pricing AI, including our new markdown optimization software, is now available to all Snowflake customers as a Connected Snowflake application, facilitating a seamless interaction from data to AI to output.

Peak is proud to be partnered with SAP, UiPath, Snowflake and AWS, enabling our joint customers to maximize use of their existing systems whilst embarking on a new journey with AI.

Generative AI is still a focal requirement for businesses

I spend a lot of my time with business executives looking to adopt AI. There’s a lot of pressure to do so but that pressure intensifies when it comes to generative AI.

Generative AI is primarily used to create new data instances that resemble the input data. Its core strength is in creating novel, yet similar, pieces of data, and its use cases include customer service, meeting summaries, data and information searching and more.

If you’re looking to optimize your pricing, ads or stock allocation, however, generative AI probably isn’t the right approach. Instead, predictive AI, which uses historical data to forecast and categorize, could be for you. It doesn’t have to be a case of ‘either-or’ though, predictive and generative AI can be a powerful pair.

I’m eagerly anticipating the release of Co:Driver into general availability on 11 July 2024. Powered by generative AI, Co:Driver is Peak’s agentic AI assistant that enables users to interrogate, analyze and better understand the outputs from their predictive AI. It’s a key piece of the puzzle in connecting human and artificial intelligence.

Imagine you’re already using AI to get your stock in the right place at the right time. The AI is shooting out recommendations for how much of each product to reorder and when, helping you to tread the line between over and understocking. With Co:Driver, your team can ask questions about your business’ data, outputs and trends, without trawling through endless spreadsheets. Even more crucially, Co:Driver can provide them with the reasoning behind why the AI has made certain decisions.

Appetite for AI in retail extends beyond personalization

In our survey of 3,000 senior leaders, 80% of those in retail were already using or working towards using AI and a whopping 99% said their budget for AI had increased over the last five years. The appetite for AI in retail is undisputed.

To date, many of the AI use cases in the retail sector have been around personalizing shopping experiences and reaching the coveted ‘omnichannel’ nirvana but we’re starting to see retailers looking for other ways to leverage AI.

With potentially millions of dollars’ worth of stock to shift each week, supply chain is well and truly in the spotlight. Personalization is an important piece of this puzzle but AI for inventory and pricing are even bigger levers.

Gartner’s recent Market Guides for Retail Forecasting, Allocation and Replenishment Solutions and Retail Unified Price, Promotion and Markdown Optimization Applications – Short Life Cycle, which both recognize Peak, highlight this evolving landscape in the retail space.

The only thing guaranteed is uncertainty

Uncertainty continues to plague businesses with supply chains. Leaders are lacking confidence when it comes to technology investments that will ease the pain. The risk of stocking out, ending up with too much stock to shift or with their tech investments gathering ‘digital dust’ is too great for many.

Gartner’s 2023 supply chain technology wants and needs survey found that the top motivating factor for supply chain leaders to invest in supply chain technology is to make decision-making processes faster, more intelligent and of higher quality, which is only possible with AI.

In April, we launched our performance guarantee for Inventory AI, our product used by businesses to forecast, order and balance optimal stock levels across their supply chain network. With a decade delivering results for companies like Speedy Hire, Marshalls and Eurocell, we’re so sure AI is the answer, we’re willing to guarantee it.

Acceleration

Our theme of the year at Peak is acceleration. Delivering value faster, developing trailblazing products and continuing to expand across the globe. It’s been a strong start to the year for us, receiving external recognition in VivaTech Top 100 Next Unicorns, Sifted 100: UKI and featuring in Forrester’s AI/ML Platforms Landscape (Q1 2024) report.

And it certainly seems as if the outside world got the acceleration memo, too. It’s clear that there’s been a shift from a lot of talk, to a lot of action – and we’re here for it! 

With a growing customer base that includes B&M Retail, PepsiCo and Nike, we’re looking forward to the rest of 2024 and beyond, as we champion AI’s adoption into the mainstream and help our customers to drive value with AI that works for their business. 

This person shouldn’t be a technical leader in disguise, it requires a completely different persona. To understand why, let’s take a look at the current top candidates: CTOs, CIOs and CDOs.

The role of chief technology officer (CTO) is said to have arisen from the days in the 1950s and 1960s, when large corporations established research and development (R&D) laboratories and needed someone to lead teams of research scientists. A well-established C-suite member, the CTO typically has deep technical expertise, particularly in architecture and software, and is responsible for the company’s technology strategy.

Later, came the chief information officer (CIO), a role that naturally evolved from the birth of the internet in the 1980s with the growing need for management of information technology, thus attracting computer science or IT management experts. The premise of the role hasn’t changed much, but as technology continues to advance at a rapid pace, the scope has widened to include a host of new technologies, including cloud-based computing, wireless communications and mobile devices, and sometimes AI.

More recently CDOs entered the scene. CDO could either refer to chief data officer or chief digital officer. According to Gartner, the former is responsible for data collection, control and governance, championing compliance and data-driven decision making in the business. A 2021 survey by PwC found that 66% of chief data officers came from a technical background, and according to Deloitte, only 7% report directly to the CEO.

Chief digital officers, on the other hand, are responsible for designing and implementing an organization’s digital transformation strategy. Forty one percent of organizations have CDOs with a solid technology background but are more likely to have a seat in the boardroom (54%).

Exposure and experience

There’s a host of highly-qualified, senior leaders, ready and waiting to take on the AI challenge, so why am I campaigning for another person to enter the fold? It comes down to two primary factors: exposure and experience. The former refers to a leader’s position in the business, specifically who they report to and whether they are a member of the C-suite; the latter to their background, training and knowledge.

It’s widely acknowledged that AI will revolutionize business as we know it. PwC reports that 22% of CEOs are worried that their business might not be viable in 10 years’ time, and 77% of them are investing in deploying advanced technologies like AI to help secure their future. Having AI represented below C-suite level diminishes its importance, something we see most commonly with chief digital officers, who typically report to a CIO or CTO. Simply put, without direct CEO sponsorship, AI can become a second-tier project, an afterthought.

Usually, CTOs, CIOs and CDOs have a technical background and rightly so. Technical experience is needed to leverage AI but oftentimes, technical folks treat AI purely as a technical problem to be solved, rather than a core aspect of a business’ commercial strategy. If AI is to deliver the transformational outcomes businesses are looking for, it needs someone to think beyond the technical capabilities.

Introducing the Chief AI officer

The chief AI officer (CAIO) is a fairly new and infrequent role. According to a LinkedIn search I conducted of titles at the time of writing this article, there were only around 2,100 CAIOs on the platform. In comparison, searches for CTO pulled over 800,000 results, CIO over 350,000, chief digital officer over 200,000 and chief data officer over 150,000.

I won’t lie, this person is going to be difficult to hire. They need a very good understanding of the technology and its potential use cases, but they shouldn’t have an IT or data science background. It’s more important that they have solid commercial acumen and are keen to drive value and efficiency from AI across a business.

Reporting to a CIO, CTO or CDO will not suffice the entrepreneurial nature of the chief AI officer, who moves fast and fails fast. They need not be burdened by technical constraints, and there should be no buffer between them and the CEO so that conversations about return on investment and opportunities to exploit AI are outcome focused, rather than bound by budget and skepticism.

This person needs to be able to lead a cross-functional strategy, but I’d argue they don’t need a large team. Instead, they need to lead with influence and embed practitioners, technical or commercial, into departments across the business. Hiding away in a research and development-style cave away from the end users is a sure-fire way to develop AI that fails to address your outcome.

The era of the CAIO is here

For the full potential of AI to be reached, it needs more than a proficient, technical champion. Instead, it needs a change agent who’s not accepting of the status quo and able to enthuse technical skeptics. Consider the era of the chief AI officer upon us.

This article was originally written and published for Forbes Business Council on 8 February 2024.

Myself and my fellow co-founder, David, are Chorlton residents and regulars at their Brookburn Road stadium. This season, we’re taking our support for West one step further with three pitchside advertising hoardings. The message for the West players is clear: Do Great. It’s a slogan used by Peak that encourages our wide-ranging customer base — which includes the likes of Nike, Molson Coors and Marshalls — to reach new heights in business using AI.

The exciting new partnership builds on our existing community outreach with the likes of FareShare Greater Manchester — best known for its campaign against food waste, championed by Marcus Rashford — and voluntary work with Manchester Urban Diggers and Platt Fields Market Garden.

About West Didsbury & Chorlton AFC

Founded in 1908, West Didsbury & Chorlton AFC – nicknamed “West” – has become the leading community club in south Manchester. Our sponsorship will support their junior, women’s and men’s teams, who play an important role in the local community.

You can see the Peak logo proudly showcased at Brookburn Road, and our shared values of high performance and inclusion were a key reason for choosing to sponsor West Didsbury & Chorlton AFC. Through this sponsorship, we’ll reach out to a passionate football community, who share these values, and the belief that football should be for everyone.

How you can support West Didsbury & Chorlton AFC

If you fancy joining us on a matchday, head down to West’s Brookburn Road stadium in Chorlton. Tickets are £7 per person and available online via Shocal or at the turnstile on the day.

On a matchday, you can expect a family-friendly environment with a great atmosphere from hundreds of supporters and a variety of food and drinks available to purchase from independent Manchester vendors. 

Check out upcoming fixtures for the women’s team and men’s team:

• Women’s team (NWWRL Premier) fixtures here
• Men’s team (NWCFL Premier Division) fixtures here.

One year on and we’re well and truly in the AI era. For businesses, the application of AI in a commercial setting is a major technology shift. From my perspective, just as businesses that failed to adapt to the internet got left behind, so will those that don’t adopt AI.

The problem is that with all of the hype, many business leaders have little idea where to start. In this year’s machine learning, AI and data landscape, there were at least 1,400 logos across dozens of categories, according to data compiled by a team at FirstMark, a venture capital firm. AI companies are popping up everywhere, each hoping to capitalize on growing commercial enthusiasm. So, what’s a business leader to do?

There aren’t many people who can say they’ve worked in the AI space for nearly ten years, but I can, and I’m here to be your signal through the noise with three actionable pieces of advice on getting started with AI.

Don’t let data hold you back

I’ve lost count of the number of times I’ve heard, “I can’t start yet. I don’t have my data sorted out.” I get it; data is the lifeblood of AI, but huge digital transformation projects are costly and can take years to complete. You really don’t want to wait five years to see any return on investment.

I recommend starting with a functional area that is both complex and data-rich. There will probably be some work to be done to ensure your data is AI-ready, but it won’t be anywhere near as painful as a business-wide transformation.

By using this modular approach to build out your AI capabilities over time, you can see a faster return on investment. Then, you can identify the next business area that will benefit from AI at the same time as building in-house expertise to support future AI projects.

Work with the outcome in mind

We’ve all been swept up in the hype of AI, and the temptation to jump in feet first is real. Before you take the plunge, though, you need to truly understand the problem you’re trying to solve or the opportunity you’re trying to address.

The simplest way to do this is to ask yourself what the outcome you’re trying to achieve is. For example, do you want to reduce the amount of working capital tied up in safety stock? Do you want your customers to have a more seamless experience talking to your chatbot?

Everyone wants to jump on the generative AI bandwagon. Its ability to produce novel text, imagery and audio lends itself well to content creation or image-recognition tasks, so there are real business benefits.

But there’s another type of AI that has been modestly serving business needs for years: predictive AI. Predictive AI typically uses structured data sets, like inventory logs or pricing data, to deduce the likely future or categorizes based on patterns. Its optimal use cases are demand forecasting, customer churn prediction and price elasticity, the type of areas that when optimized by AI can be game-changing to business fundamentals.

Understanding your desired outcome and the type of AI that will help you achieve it will make the landscape of possible solutions much easier to navigate.

Think longer term

Let me ask you a question: Would you cut and paste someone else’s website and use it for your business? Maybe you change the color scheme a bit, tweak a few words and add your logo? You’re likely shaking your head at me, “No, Richard, don’t be a fool. My website is the storefront of my business. It’s vital that it represents my brand and works exactly how I need it to.”

You’re right. Every business is unique, with different target customers, supply chains, people, practices and more. Each has its own set of challenges and opportunities.

Think about AI in the way you think about your website. To really make a difference, AI has to understand your business and leverage its uniqueness. To gain a true competitive advantage, you need your own AI.

That doesn’t necessarily mean you need the in-house capability to build it. The idea of developing your own AI can sound laborious and long-term, which is what makes point solutions — services, tools or products that solve specific business problems — so attractive.

Fast forward five years’ time, though, and you might find yourself picking apart dozens of point solutions that have become obsolete as new technologies have developed. Instead, look for tools you need to develop, and adapt your own AI solutions over time.

One year on from AI’s “iPhone moment,” there’s still immense pressure for business leaders to jump on the AI bandwagon. So, as you sit down to work on next year’s strategy, don’t let the thought of AI overwhelm you. Pick one data-rich area, understand the desired outcome, and find a solution that allows you to expand your use of AI over time. That way, you’ll be setting your business up for a long and happy future.

This article was originally written and published for Forbes Business Council on 12 December 2023.

What is generative AI, and why is it hogging the headlines?

Generative AI is a type of artificial intelligence that uses deep learning algorithms to learn from huge amounts of content based on billions, sometimes trillions of parameters.

It generates things like images, videos, audio, and text by learning from patterns in the data it has been trained on.

The algorithms that drive generative AI tools have been in development for some time, and some projects in beta have been made available to consumers.

Companies like OpenAI (the creators of ChatGPT) have productized, packaged and marketed their tools expertly, clearly with the aim of gathering a huge userbase. And they delivered on that aim, with each tool boasting millions of users.

It’s no surprise. Who could resist the temptation to type in a prompt and see the results of its complex algorithms in just a few seconds?

These tools can show consumers the power of AI algorithms in just a few seconds. Even better, it’s showing you that power in a way that’s relatable to most people — communicating through word and image.

But it’s not just curious consumers tempted to these tools, businesses are recognizing the potential use cases, which are really exciting.

Whether it’s creating smarter chatbots, enhancing copywriting and design, accelerating work on software development projects or integrating explainability into AI models, there are clear and compelling use cases for generative AI.

I’m personally really excited to see how generative AI can enhance our AI applications in the near future.

But I’m asking you to forget ChatGPT, forget DALL-E and all the other attention-grabbing generative AI tools for a second. Here’s why.

Is it time to forget ChatGPT for now?

Generative AI is really good at certain things, generating hype is one particular strength. But the hype around this AI is a double edged sword.

On the one hand, it gives AI a much-needed boost in public interest. But on the other hand, the extravagance of generative AI can distract from the value of commercial AI, what the Economist recently called “boring AI”.

This isn’t the sort of AI that hits the headlines with ease. This is the type of AI that’s been modestly serving business needs for years. It’s the type of AI that, if effective, consumers wouldn’t even know was there.  

But the impacts of this AI are real. Boring AI can increase efficiencies across your value chain, reducing your cost to serve. It can give your customers a personalized omnichannel experience, driving up key metrics like customer lifetime value.

It can help you set the optimum price for your products throughout each product’s lifecycle. It can optimize decision-making across your business, including when and what technology you invest your time and capital in.

This AI is game-changing to business fundamentals. It can’t write you a Mother’s Day poem, but it can give your business exactly the boost it needs to win in a competitive market.

For those who’ve had their interest in AI heightened by tools like ChatGPT, the real question shouldn’t be “how can we get an equivalent tool in our own business?” To deliver truly game-changing AI, we need to take a step back from the hype of generative AI and understand what’s happening in our business.

So where should I start with AI?

That’s why every AI journey should start with an assessment of the opportunities and weaknesses of your business. It’s only from this vantage point that you can see which areas should be prioritized and know what AI solutions might fit.

Many businesses assume the next step on their AI journey is to modernize their data infrastructure. Often this is because they assume their data quality is too poor to be AI-ready.

But data infrastructure projects can be costly and take years and, with AI competition heating up, most business can’t wait years. The good news is you don’t have to. Your data doesn’t have to be perfectly organized in a data warehouse to be AI-ready.

We’ve built our Peak platform to work with all kinds of data, from enterprise data warehouses to single datasets, meaning you can get started right away use Peak as your data platform, too. Or simply plug Peak into your existing data platform.

Before trying to integrate generative AI into your products, it’s important to first explore how other types of AI can help you make and automate great, data-driven decisions.

You can start small with AI applications, and add use cases over time. For instance, many of our customers get started with AI-powered demand forecasting or customer segmentation. From there, they add additional AI capabilities like AI-driven recommender tools or inventory management.

The really cool thing is each application enhances one another, and combines into a single connected AI that levels up every part of their business.

We’ve worked with businesses who’ve seen incredible results through so-called “boring AI”. Whether that’s a 28% uplift in email revenue, a 73% increase in recommender-driven average order value (AOV), or using AI to make stock distribution decisions in one hour that used to take them one week.

To business leaders, these outcomes are far from boring.  

So yes, generative AI is really exciting. I’m personally looking forward to the opportunities it brings Peak to level up the explainability of our AI applications. But, for now, forget ChatGPT; forget generative AI, forget any particular solution. First, use your data to fully understand your business, and let boring AI help you.

This will give you the necessary foundations for further AI investment: an optimized business, with the data and tools it needs to know when to invest in the next big thing. 

So, maybe boring AI isn’t so boring after all?

So, what does this funding mean for our community?

It means we’ll be bringing the power of Decision Intelligence to more and more businesses around the world, further democratizing AI in the enterprise and growing our community as we do so.

This funding also means we’ll be investing even more into our product and R&D initiatives. As we’ve grown, the true power of AI to transform the way companies operate has become even clearer. Our platform is driving transformational results for our customers and gains that are adding millions to the top and bottom line of many of your businesses.

This is because the Peak platform is built like no other. It puts AI in the hands of business users directly through our suite of Decision Intelligence solutions, while enabling data teams to work at a pace and scale they can’t with traditional tooling and infrastructure. We’ll be investing heavily in new platform features and capability, such as our recently announced data bridge for Snowflake, to give our customers even more power to solve their hardest problems and create the future on Peak. 

To achieve all of this we’re working hard to grow our team and to develop our talent, globally. We hope to welcome more than 200 new Peakers in the coming 12 months as we grow in the UK, India and USA.

What’s more, we’ll also be celebrating our community at AltitudeX on November 4th, our new conference bringing commercial leaders, data scientists and engineers together, all under one roof. Come and join in the fun!

On behalf of everyone at Peak, thank you for being a part of our community. Thank you for being part of the Decision Intelligence movement. Thank you for making this journey such a fun and exciting one. 

Oxx led our Series B round, with all our existing investors participating. This brings our total funding to $43m since our seed funding in 2016. We’re also welcoming Oxx General Partner Richard Anton to Peak’s Board of Directors. This is a significant milestone for our team and our company. Here’s what we’re planning next. 

Decision Intelligence is really here.

Decision Intelligence is the commercial application of AI to grow great businesses. This is because, at its heart, AI is a technology that helps make decisions. In the case of running a business that means consistently great, highly optimised commercial decisions that can be made instantly, continuously and handle complexity beyond that of human cognition. Businesses who are harnessing this capability are growing faster, with higher margins, than their competitors. In business, who wouldn’t want to do that? 

For this reason, more and more businesses are choosing Peak to make their Decision Intelligence future a reality, today. Industry leaders across retail, consumer goods and manufacturing, as well as some of the world’s most famous brands, are all trusting Peak’s Decision Intelligence platform to make decisions with them. In fact, Peak is processing 570TB of data, making 200,000,000 predictions and 2,600,000 automated decisions for our customers every single day. It is hooked into data sources across these businesses to help support a connected Decision Intelligence capability that no software product has ever enabled before. 

Decision Intelligence is, therefore, really here. We’ve even made a little video to celebrate ?

Our next chapter

Our mission as a business has always been to help our customers do great things with data, while building a company that everyone loves being part of. And by everyone we mean our team, our customers, advisors, investors and everyone connected with our company. 

With this new funding and our continued growth as a business, we’re starting a new stage in our journey. We have all the foundations in place to make our own significant dent in the world; by helping our customers change the way they work and by building a tech company of the future ourselves. Our next stage will focus on our product, going global and continued growth of our team and culture.

1. Building an era-defining product

With more and more businesses running on our platform we are beginning to see in sharp focus the incredible power it brings. The platform embraces the uniqueness of every business. It amplifies this uniqueness as competitive advantage in the form of a unique AI created for each company that runs on it. Because of this, the possibilities for Peak are endless and our roadmaps are focused on continually adding value for the companies that trust it to be a core part of how they work. 

We’re planning to add more capability and features into Peak’s application stacks. We want these applications to be the way businesses gain commercial advantage from running on Peak. We are also making heavy investments in our platform capabilities. We want Peak to become the standard for Decision Intelligence in the enterprise. 

To do this we’ll be expanding our Engineering and Product teams, ensuring we continue to grow a unique and world class team that operates on the cutting edge of B2B software. 

2. Scale, globally

In 2020 we grew organically outside of our home market in the UK. We now have customers in the US, Europe, India and the Middle East. Through 2021 we’ll be opening new locations in both the US and India to support this commercial growth and to help us best service our customers in these regions. Our new location in India will be our second office after we opened an Engineering base in Jaipur all the way back in 2016. We’re really proud of our Indian heritage and are excited to be growing our team here.  

3. Growing our team and culture

In a relatively short time our team has grown to 175 Peakers. We’re incredibly lucky to have such a great collection of minds, personalities and talent, all of whom live the values of Peak every day. This has seen us recognised as one of the top 100 companies to work at in the UK; an award we’re extremely proud of. Central to our culture is inclusivity and diversity, and we’re also proud that our team includes 53% more women proportionally than the average UK tech company.

As we grow as a company we’ll be staying true to our culture. We’ll be looking to develop our talent and teams, as well as to hire some of the very best talent from across the world of tech. We’ll be looking to hit even more ambitious and important inclusivity and diversity goals and we’ll continue to foster a culture that we are all proud of. Plus, of course, we’re relishing the prospect of operating in a post-pandemic world, and finally getting our team back together in our offices!

Whether you’re reading this as one of our valued customers, a partner, a colleague, an investor or an interested observer, thank you for making Peak what it is today. I’m really looking forward to the next stage in our journey together.

Why?

There are three profound, fundamental, themes that are shaping the future of work. The combined effect of all of these will change and, ultimately, revolutionize the way all of us work inside every business.

1. Data infrastructure has reached a maturity that democratizes the use of artificial intelligence technology
2. Using artificial intelligence technology is a recognized competitive advantage in business
3. The economic opportunity for pure play disruptors to enter the market and supply this product is huge

Businesses will, therefore, win by consistently applying artificial intelligence to their work. Given the high technical barriers to access (more on that later…) they will search for partners who can harness that data and turn it into a valuable outcome. This value will be created by applying artificial intelligence to the most important function of a business: its decision making. 

This is because, at its heart, AI is a technology that helps make decisions. In the case of running a business that means great, highly optimised commercial decisions that can be made instantly, continuously and handle complexity beyond that of human cognition. Businesses who are harnessing this capability are growing faster, with higher margins, than their competitors. They are winning. In business, who wouldn’t want to do that? This is Decision Intelligence.

We’re in the Intelligence Era

In established markets, businesses are often known to be cautious, sometimes risk averse and favouring the tried and tested over the new and exciting. Well, that was the old way. There is a new game to win now; that game is the Intelligence Era. This ‘4th Industrial Revolution’ will be marked by a step change in the pace of development and transformation within the firm. Old businesses, businesses that have won in the last era, will need to ‘unlearn’ the 20th century methods and start rapidly adopting the 21st century perspective.

Organizations who have embraced the power of data, insights, and automation – this new game – are already winning over new customers and dominating their industries. It doesn’t take much to glance at the headlines of every national newspaper to work out one common theme.

They use artificial intelligence technology to make great business decisions. We call this superhuman power, Decision Intelligence. Decision Intelligence is the commercial application of artificial intelligence technology to enhance business decision making.

Peak’s mission is to put Decision Intelligence into every business, globally. To change the way we work. To help our customers make that change. We have started well, but our journey has really only just begun.

Great business decisions, all the time

Businesses that make great decisions win. These could be great marketing decisions, great product decisions, or great supply chain decisions. The combination of these, made well, drives overall success as a business.

We have become accustomed to using data to help inform decision making. The next logical step is to use intelligence to inform decision making, and in many cases, to make decisions alongside us; quicker, faster, continuously over more data, more often.

Peak is built to provide this capability. Our customers love this. Nike, AO, PepsiCo, ASOS, KFC…These household name brands and respective industry leaders share our perspective and they know the opportunity to expand, to create this category for businesses to thrive, is now. The Intelligence Era is now.

Decision Intelligence at scale

We mentioned it briefly; but it is worth revisiting. Now, more than ever, every business is data-rich. This data is a history of every decision made in a business, and every outcome. It records the activity of every individual and group within these core business functions as they carry out their daily decision making. A truly transparent and clean record of what has driven success in a business and what has failed. This is the first thing you recognize if you are to win in the Intelligence Era. All the information you need is right under your nose.

Decision Intelligence works by taking all of that information, that data, and looking for patterns. Patterns of success, patterns of failure and identifying where the ‘margin calls’ can be made; where the business can be optimized and enhanced in order to drive growth and profit. It learns, it compounds, and it improves its output on every iteration. But to do this you need a new kind of software platform to run on – and at Peak we have our platform.

Now, in the past, you may have scoffed at the idea of taking a company’s entire data history and using it as an input to a statistical model. “It’s just not possible.” Well, today, it is. With data infrastructure every rapidly increasing, the architecture is taken care of. Statistical models, although useful, are not appropriate here. You need artificial intelligence platform, like Peak, capable of processing it at scale. Problem. What problem?! In fact, it’s only step one of the additive value creation to the business.

On top of that, the platform will need to give end user outcomes into the workflows of these expert operators, be they supply chain managers, product and customer lifecycle owners or digital marketing experts. The decisions they make are constant, and they are high stakes. What price do I list this item at? How many should I buy from the supplier? How often should I replenish our warehouse? Where do I best place my next marketing dollar? To make these decisions it mandates a slick user interface as a must, and a high degree of automation. Constant, clear and consistent decision making. Again, both are possible, in one platform – and that platform is Peak.

Beyond the optimization of a single business, connecting the enterprise through Decision Intelligence, lies perhaps an even more profound opportunity. That is to connect businesses to one another, many to one, one to many; a network of companies learning from one another and the decisions they take to succeed, and ultimately dominating their industry. To do this you need a platform – and that platform is Peak.

Peak shifts the paradigm for all businesses

Given the nature of disruptive innovation, this change will happen rapidly. It will happen over months and years, not decades.

The early adopters will seize this advantage and use it to dominate their industries and create unassailable intelligence moats. They will partner with key suppliers and buyers to create their own intra-industry network effects, powered by the proliferation of Decision Intelligence in everything they do.

At Peak, we are designing our business and our platform, to enable this rapid customer adoption. To remove as many of the barriers that businesses face when adopting new technology and to make it as results-driven and human-centric as possible.

Peak is built as a full stack Decision Intelligence platform. Businesses who have attempted to build this capability themselves can often struggle on account of the complexity and expertise required. A tech company is yet to offer an all in one solution, which has led to many various organic systems being created, pieced together from a variety of technology providers, from databases, ML platforms to BI front ends and everything in between. This ‘vendor soup’ historically causes more headaches than it solves. Accountability can often go AWOL. We want accountability – so we built Peak as the full stack.

That solves the technical headache and gives a business the power it needs to win in its industry, but given we are changing the way we work, supporting this change is of paramount importance. So, at Peak, we bundle two often-overlooked elements of a transformative journey: industry expertise and implementation. No one wants to ‘talk IT’ to line of business and no one wants to ‘talk line of business’ to IT. We get it. So, we talk both. Our implementation teams focus on outcomes, generating value from Peak, for our customers. And our industry experts think long term; a strategic focus to help you compound your wins over time and create an unassailable advantage.  

We get very excited about this journey. About what the world could look like in just a few years. About how we can all be a part of that and how going to work can be exciting. Really exciting! A place where we can work together and celebrate our everyday success. Celebrate the decisions we make. Let’s win.

If any of this interests you, we’d love to talk. It could be on anything. We are open and invite views on the future of work in the intelligence era from any and everyone.

According to a recent Gartner press release, “Gartner research shows that 77% of retailers plan to deploy AI by 2021, with the deployment of robotics for warehouse picking as the No. 1 use case.” I’ve spoken before about our belief that we’re entering the AI era – and that it’s our mission to help businesses do great things with data to compete in this era. To us, it’s fantastic to have our work recognized by Gartner, as we continue to look to make AI accessible for all retail businesses.

Retail, as an industry, is ripe for AI adoption. Given the vast amounts of data a retail business produces the potential AI technology brings the industry is huge. Our work with the likes of boohoo, Fred Perry and Footasylum demonstrates this, with these businesses achieving game-changing outcomes from taking an AI-driven approach. However, for many retailers, being in a position to successfully adapt – and derive value from – AI is challenging, if not impossible.

Why we think we’re cool

The Gartner report states that “The future of retail is found in agile flexibility, based on the understanding of customer expectations, innovation and continuously delivering more value for customers.” We believe that the key to making this happen is by introducing a centralized system of intelligence into a retail business’ core.

In order to help retailers achieve success in the AI era, we’ve built a brand new business system – the AI System. It centralizes intelligence and puts data to work across the value chain. It’s able to leverage data from across an entire retail business to eradicate silos and power business-wide optimization.

Without such a system, retailers looking to introduce AI will struggle to keep up and realize their true potential. The current software market lacks scalable AI infrastructure, integrations and support services, making any attempt at harnessing the technology slow and frustrating. We believe that a new way of thinking, and a new type of enterprise business system, is required.

We see this latest recognition from Gartner as further validation of both our approach and the work we’re doing in the retail space. It’s another key landmark on our journey to enable all retailers to do great things with data.

Gartner, “Cool Vendors in AI for Retail,” Robert Hetu, 29 May 2020

Gartner Press Release, “Gartner Predicts At Least Two Top Global Retailers Will Establish Robot Resource Organizations to Manage Nonhuman Workers By 2025,” February 4, 2020, https://www.gartner.com/en/newsroom/press-releases/2020-02-04-gartner-predicts-at-least-two-top-global-retailers-wi

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

Firstly, we wanted to ensure the business was on a strong footing going into 2020, even before the tragic spread of coronavirus. From a financing perspective, this meant having the capital to fuel our growth plans and the R&D investments we are making in our AI System and core technologies. Now, more than ever, I’m glad we did that. 

Secondly, and perhaps more importantly, the very heart of Peak’s mission is to help all businesses do great things with data. Practically this means being able to compete in the AI era; to transform and embrace the potential that data and AI brings. That potential is huge, as our work has shown over the years, with many of our customers achieving significant increases in revenue growth and profit margins. Making that shift, however, is hard. For many businesses, it is unattainable. 

Yet our mission means enabling every company to be great in the AI era. That’s why we’re continuing to invest in both our technology and our team; to make AI accessible such that our customers can make the leap to becoming AI companies themselves. 

Our AI System is already at the forefront of a brand new market for enterprise AI systems and is developing at a rapid pace. Over the coming months you’ll continue to see more new product releases and new features added thanks to the continued hard work of our team and the amazing feedback we’re getting from our customers. 

I wanted to take this opportunity to say a huge thank you to our customers, and our team, our investors, our partners and everyone connected to the Peak team. It’s great to be on this journey with you. 

Take care and stay safe.

Richard

More from Peak…

 Why the AI System is the future of the enterprise

? Peak secures $12M extended series A investment to power AI System

? Peak secures its spot in The Sunday Times Top 100 Small Companies to Work For

? We sat down with Intel for an AI fireside chat

To put it into context, in the same way that business functions demand their own ‘System of Record’ – sales and marketing have CRM, operations have ERP – AI is now so fundamental to the enterprise that it demands a new system. We call this the enterprise AI System. 

The AI System will power decision making at every stage of a business’ value chain. It won’t be constrained functionally like current workflow systems, and it will consider the global optimization of a business as its primary goal.

Without this new system, harnessing the true power of AI will simply not be possible. The current software ecosystem means that there’s a distinct lack of scalable AI infrastructure, which creates dispersed data across the enterprise. There’s also nowhere to deploy AI in an end-to-end workflow, which means the process of building AI solutions becomes laborious and slow. On top of all this, there are insufficient integrations and support services – which means managing AI’s success is just about impossible.

A new way of looking at enterprise architecture is required, alongside new technology to power that new way of thinking.

Getting to know the AI System

For any business leader looking to supercharge their enterprise using AI, there are some fundamentals that you simply have to establish, fast. You have to eradicate data silos, bridge the gap between disparate systems, put intelligence at the very core of the business, and actively push it to deliver actions and outcomes.

Each of these core pillars will serve value to the organization in more ways than one. Think about it; what would you do with all of your data in one place? What if you knew how a change in marketing spend would impact your supply chain? What if you could rapidly test, learn and improve your decision making? The intelligent combination of all of these underpins the AI System, which further multiplies the value it offers an enterprise.

No silos

Peter Thiel describes data network effects brilliantly in his book, Zero to One. To paraphrase; companies that harness data to gain a competitive advantage create a flywheel effect, where their ability to service customers is enhanced. This leads to them winning more customers, generating more and more data as they grow, which, in turn, reinforces their advantage. This data network effect can be used to capture the majority of a market’s economics (profit) and see companies go from – you guessed it – zero to one.

This is why it’s absolutely crucial that you eliminate all of the data silos in your business.

AI has the unique ability to consume data on a scale that we’ve simply never seen before. In order for it to excel in its decision making, AI needs to access as much data as possible. Walled gardens of information have been created in order for us mere humans to be able to consume the data in manageable, bitesize chunks. This means that decisions are made – decisions which affect the whole business – often without the right information being taken into account. More often than not, this leads to unintended consequences and less-than-optimal outcomes.

The reason I use the Thiel example is that exposing AI to as much (useful) information as possible allows it to understand the game you are playing in, as a business. The more data you provide AI with, the better it becomes at recognizing patterns and predicting outcomes. In the same way that humans learn from experience, you could argue that AI behaves in a similar way.

Innovative companies like Dremio have recognized this as a ‘must do’ for businesses who want to win in the AI era. Their ‘Data Lake Engine’ abstracts away the need for warehouses, cubes, aggregation tables and extracts. The output from ‘engines’ like this will feed directly into an AI System, creating immediate opportunities to drive real business outcomes.

By gathering more data, and by presenting that data in the right way, you are giving the AI an advantage to make more informed decisions. The more informed decisions you make, the more data the AI can learn from, and so on and so forth. It’s a data network effect – but it all starts with eliminating the data silos in your business.

Centralized intelligence

At some point during our careers we have sat down to an Excel spreadsheet with more rows and columns than grains of sand on the earth. We have saved that spreadsheet, emailed it, copied it, adapted it and only then (plus a few more circles of that chain) made a decision on it. It took months to build, another month to gather the feedback and another month to make those decisions a reality.

Why? Because we had no access to a central intelligence. As businesspeople, we created a system that got the information needed to make a decision into the hands of the people as quickly as possible. The problem was – it was still painfully slow!

Centralized intelligence flips this concept on its head. Rather than passing the ‘intelligence’ from team to team over the course of many months, we need to bring the teams to the intelligence. You need to create a decision making and information hub that all teams can use, simultaneously – exposing immediate clarity, pace of action and visibility of outcomes across the organization.

The problem at the moment is that many software solutions, from customer email to warehouse management systems, are created to follow this ‘conventional’ human workflow – a workflow that we just identified as being oh-so problematic to rapid growth.

AI changes this relationship with software and systems. It allows all of these diverse systems to communicate, and it allows all of these systems to become a key input into centralized intelligence. But, this centralized intelligence has to reside somewhere, in a new system – an AI System.

We’re working with businesses who were stuck in the old way, but, by shifting to a centralized intelligence model, we’re helping them do great things. Take our customer, boohoo, for example. Within the last 12 months, the fast fashion giant has moved to a centralized intelligence powering core functional teams. They just did this.

Actions and outcomes

As businesses we live and die by our P&L, and as business leaders we live and die by our decisions that affect that. It’s our responsibility to take actions and drive outcomes that positively influence this. We empower our teams to do this, and good management is about how effectively we make this happen. Why then, as technology leaders, do we allow 80% of data projects, according to Gartner, to fail? The answer – because they are not focused on actions and outcomes.

By its very nature, AI is focused on outcomes. It’s built to solve problems and to answer the ‘why’, but, more importantly, drive the ‘so what?’

It learns by understanding its decisions, making improvements on them and then iterating that process. For that reason it is paramount to ensure that AI can power as many decision making processes as possible.

As it stands, the enterprise ecosystem makes it very difficult to put AI solutions into your workflow systems and drive outcomes. The technology was created at a time when this was not a reasonable demand of its functionality, but now it is.

Footasylum, a UK streetwear retailer, was an early adopter of this actions and outcomes first approach. In using the Peak AI System, the business drove an increase in digital marketing revenue of 28% YoY. But that was just the start. Footasylum quickly realized that this centralized AI was capable of powering its acquisition strategy, too. In integrating with its acquisition platform, Footasylum was able to increase its average ROAS by three times the current level.

As the Footasylum story shows, you need to integrate and push the decisions made by the centralized intelligence into these systems of engagement in order to benefit from your AI-driven decision making. Your AI System has to be agnostic to integrations; able to connect seamlessly with any other system in your organization.

Businesses like Tray.io have identified that this ‘glue’ is going to hold these systems of engagement together with their centralized AI Systems, by creating a centralized automation platform. Gone are the days of buying tin and wire for your basement – these are the decisions that technology leaders are taking to ensure they are ready to drive outcomes in the AI era.

Summary

To summarize, it’s clear that, as businesses, we must all adapt if we are to grow and win in the AI era. This will mean a new way of thinking about our enterprise systems and architecture. The exciting part, we believe, is that these new systems present us with an opportunity to create growth on a scale that we haven’t experienced before.

We are already seeing AI-powered businesses take advantage of the transformational benefits the technology offers them (UK retailers are using AI to grow 30% faster than their peers, with 50% higher profit margins). There is no question that we stand on the edge of the AI-era. The time to act, for those not in the game already, is now. 

More from Peak…

? We’re at the dawn of the AI era. Find out why in this note from CEO Richard Potter

? Peak secures $12M extended series A investment to power AI System

? Peak secures its spot in The Sunday Times Top 100 Small Companies to Work For

? We sat down with Intel for an AI fireside chat

When Dave, Atul and I founded Peak we had a very clear idea in our head of what we wanted to achieve. Our mission, ever since, has been twofold; we aim to help businesses do great things (with data and AI!) and to build an amazing company – one that everyone loves being a part of. 

The culture we’ve created at Peak makes the business what it is. Of course, business has changed since the early days when just a handful of us were sitting in a co-working space on Deansgate, to the 100+ strong global company we are today. However, that initial culture continues to be woven into the fabric of Peak, and it’s amazing to see our commitment to this recognised on a national level. 

After our seed funding round a few years ago one of our first decisions was to bring somebody in who understands what makes a business tick in terms of people and culture. Lucy Tannahill joined us as our Head of People and has been instrumental in shaping the culture and spirit of Team Peak and the rest of our devoted People team.

Whether it’s end-of-quarter events, team bonding trips to the Peak District or even just Friday beer o’clock in the office, we’ve always aimed to make Peak a place that our team enjoy coming to every day. Of course, we make sure that the hard work gets done, but we have some fun in the process, and that’s really important. For me, a great culture and a great team trumps any kind of business strategy – it’s the number one reason that we’re where we are today.

I often describe our aim at Peak to create a sustainable high performance culture. Here’s some of the mantras we live that help us do that:

• Family first; nothing is more important
• Team over individual 
• Coaching over telling 
• Always put the customer first (at work) 
• Success is not guaranteed and everything must be earned
• Move fast, make quick decisions, correct as you go 
• Respect colleagues – everyone has a genius 
• Don’t shy from hard conversations  
• Be great, not good (and hold each other to high standards) 
• Always take responsibility (be leaders, at every level) 
• We all own Peak. We are all responsible for our culture and success 
• Nobody is more important than the business. We are a team of equals 
• No politics, ever. Politics are bullshit 
• No excuses, be honest with yourself 
• Always help a colleague in need
• Do that extra thing, today 
• Don’t lose sight of the bigger picture opportunity 
• Have fun, don’t take yourself or work too seriously 
• …cash is king. Do not waste company resources 

That list might not be for everyone, but it is core to Peak. It’s authentic and guides us. That would be my advice to any business leader looking to put culture at the heart of their mission. It must be authentic, it must be real and you must live your values everyday. Our values are published here and for everyone to see – we hire to them, we coach to them and we reinforce them continuously. Values can’t be simply nice sounding buzzwords, as so many are. 

For us, we’ll keep working hard to build on this strong foundation. I hope we can and that we build Peak into a global top 100 company to work for one day… 

On the Sunday (yes, Sunday!), I spoke alongside Footasylum’s Tom Summerfield and Tom Litchford from Amazon Web Services (AWS). We discussed the importance of cutting through the noise and the hype that surrounds artificial intelligence (AI) in the retail space and focusing on the real, lasting, uplift it can bring to the modern retailer. 

TL;DR — AI can optimise your entire value chain, end to end. Those who embrace it will outcompete everyone else because they will service their customers better. To do this requires the right technology architecture and a centralised, full stack, AI System is the right way to take the leap. Faster, smarter and with real business outcomes. 

Since the event, we’ve had loads of requests for the slides so here they are. Hope they are thought provoking and helpful:

The event also gave us a great platform in which to announce some of our latest news to the world. We’re thrilled to have secured AWS Retail Competency status, another string to our bow having been awarded the Machine Learning Competency accreditation the previous year. Well done Peak team. 

Aside from the keynotes (great) and checking out the latest and greatest from the cloud computing world, we also had the honour of presenting alongside AWS, Intel and our customer – and good friends – Footasylum.

Our presentation focused on the notion of direct-to-consumer businesses being able to offer truly personalised, connected retail experiences to their customers – all by leveraging their vast amounts of data with the power of artificial intelligence (AI) and machine learning (ML). 

Given the nature of the event and its audience, re:Invent also provided us with a great opportunity to get under the hood of the Peak AI System. Our unique full stack approach to AI is going to be the key for most companies as they look to place AI at the heart of their enterprises – enabling rapid deployments, tangible results and upgrading the entire systems landscape at the same time. 

Check out the recording below and don’t forget you’re watching the future of the enterprise!

1. Pricing optimisation

Price elasticity is something that companies with limited stock have measured and optimised around for a long time – think airlines and hotels. However, AI can take such techniques and strategies deep into the retail sector, helping retailers determine the optimal price to sell products based on their preferences. For example, you can optimise price for volume or margin. You can offer limited time only discounts precisely to move certain products, and you can use competitor pricing and price elasticity to ensure profits are maximised and market share maintained.

This is useful for retailers in the services sector, where consumer choice is lower, and pricing is controlled by you as a brand. For general retailers, in the fashion space, for example, price optimisation can be very powerful when it comes to shifting slow moving stock or maximising the profits from end of season sales.

2. Share online and in-store learnings

One of the advantages of e-commerce is that the virtual store can be changed and adjusted continuously. And, crucially, it can be personalised for everyone. This isn’t possible in-store. However, learnings from the behaviours of customers online can be taken in-store, helping retailers optimise store layouts, the positioning of products, and even the customer experience.

At Peak, we see this as one of the big changes about to hit the retail sector. The very purpose of the physical store is beginning to change and – while it should always have been about customer experience – many retailers placed product range and choice ahead of experience for a long time. Now that the internet offers unlimited choice, the purpose and use of stores themselves will change and, enabled by AI-driven insights, they can be optimised to produce the ideal customer experience.

3. Forecasting demand

Demand forecasting is hugely valuable to retailers who are looking to fulfil customer demand in an optimised way. It can ensure that sales opportunities are never missed and that inventories are optimised, which frees up valuable working capital to further invest in sales growth.

One additional benefit of being able to predict demand precisely is the ability it provides to optimise the promotion of goods inline with forecasted sales – in other words, a truly joined up retail model. What we mean by this, by means of illustration, is the ability to predict softening in demand for a particular product ahead of time and, in turn, automatically promoting that product to the individuals who are most likely to purchase them at any given point in time. This results in less excess stock, a faster turnover of products and fewer items being sold on promotion.

4. Customer care

This is one area in particular where artificial intelligence is already playing a crucial role for a lot of businesses, as more and more companies harness the power of AI to provide customers with responsive, attentive customer service.

The rise in popularity – and the improved efficiency – of chatbots has been extremely noticeable in recent years, and it’s a trend that will only continue to go one way. International parcel delivery business DPD now sees a third of all “live chat” interactions with customers entirely handled by its AI, which is capable of dealing with a vast number of increasingly-complex queries, yet is also smart enough to know when human interaction is still needed. Offering the faster resolution of customer issues and with the added benefit of being available 24 hours a day, 365 days a year, chatbots and other types of virtual assistants have a major part to play in the AI-driven future of the retail industry.

5. The fully-automated, omnichannel retail experience

So, given everything that we’ve covered in both of these blogs, what does the future of the omnichannel retailer look like? Well, we’d suggest looking no further than the Amazon Go concept store, which uses AI and computer vision to create a frictionless retail experience. Customers scan their mobile phones (specifically the Amazon Go app) at turnstiles to enter the store. Computers then track your movements through the shop, identifying when you have placed an item in your basket (or if you’ve put it back on the shelf). When you exit the store, you are automatically charged via the same app. What’s even cooler is that the store layout can be optimised based on customer behaviour, and replenished automatically based on real-time demand.