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The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. How do big companies evolve? How do they learn to do something new? These are questions that have taken up untold pages of books, magazines, and journal articles. As a venture capitalist (VC) in water, Ive seen firsthand that most large companies in the sector struggle to effectively engage with external innovation, particularly with entrepreneurs developing technologies that could enhance their value propositions or product suites. Yet, both sides stand to gain: Large companies expand their product suites without having to build from scratch, and startups gain access to something invaluable: distribution at scale. Thats what makes Xylems success with Xylem Innovation Labs such an impressive case study. Formed in 2021, the program was a deliberate effort to bridge this gap, engaging with the growing ecosystem of water entrepreneurs and investing in the best talent developing industry solutions. If you think entrepreneurship is hard, try corporate innovation. A model that works Building a new function within a company requires navigating the constraints of an existing organizational structure. Simply tacking on a skunkworks team with a Gone in 60 Seconds-type team of innovators often leads to fragmentation, internal resistance, and ultimately, failure. Xylem Innovation Labs avoided these pitfalls by structuring its program with precision and purpose, making it a model for systematic change. At its core is the Partnerships Accelerator, designed to fast-track the introduction of breakthrough technologies that address critical challenges for water utilities, industrial water users, and communities worldwide. Each year, the team surveys the entire company to identify strategic gaps that technology could help fill in. They then scour the global startup landscapeworking with partners like us at Burnt Island Ventures (BIV) and Imagine H2Oto find companies with the right solutions. Applications are then reviewed across Xylems business units, and a committee that includes members of the companys C-suite (this is a $8.6 billion revenue company, after all) makes the final selections. Once a startup is selected, it gains direct access to Xylems leadership and expertise, with a dedicated team member acting as a guide through the corporate landscape. They then embark on a year-long Partnership Accelerator program that not only develops their partnership with the company but a path to the broader market. The program is defined by its speed and transparencywe all know that startups dont have the luxury of waiting years for a decision. When a no comes fast, its never a “no forever”its about timing, potential, and mutual fit. This founder-friendly approach makes it one of the most effective corporate innovation models Ive seen. Breakthrough partnerships and lessons learned Since its 2022 launch, the Partnerships Accelerator has engaged over 45 companies from 14 countriescontributing to real progress across the water innovation ecosystem by accelerating solutions, relationships, and learning. Nearly a quarter of these startups have formalized partnership agreements with Xylem, while a new cohort are just beginning their journey. This isnt just about numbers; its about tangible progress in tackling some of the most pressing water and public health challenges of our time. The potential for transformation is significant, and initiatives like this are setting a new standard for how large companies can engage with startups to deliver meaningful change. Take Aclarity, a BIV portfolio company that developed an electrochemical oxidation process to destroy forever chemicals (PFAS). After participating in the 2022 Xylem Partnerships Accelerator, Aclarity continues to collaborate with Xylem to bring its technology to market. Other partnerships have already led to new product launches, such as eoapp Aqua, a satellite-based water quality monitoring tool that debuted in the U.S. in 2024 as a collaboration between Xylem’s YSI brand and EOMAP, a German remote sensing company. For BIV, partnering with Xylem isnt just strategicit has reshaped how we approach venture investing in water. Xylem collaborates with a global network of more than 40 open innovation partners, including universities, research institutes, accelerators, VCs, and end users. This extensive reach gives us an edge in sourcing high-potential startups, but this isnt a one-way street. We share promising startups with Xylem, and nearly half of our portfolio companies have engaged with Xylem in some capacity. The result? A stronger ecosystem where startups have a direct path to commercialization. The buck doesnt stop here Xylem Innovation Labs isnt just coasting on its early successes. In 2024, Xylem expanded its corporate venture investing plans to support emerging companies and water services providers, complementing its existing investments in BIV and Westly Group. More importantly, its now deploying capital into high-impact, frontier markets through its work with WaterEquity. This holistic approachcombining partnerships, investments, and strategic innovationis creating a powerful engine for scaling water technology solutions at an unprecedented pace. And the impact is growing. A self-reinforcing funding and innovation flywheel is now in motion for early-stage water companies. Four companies from BIVs Fund I have already advanced to Series B funding, and weve since launched Fund II and Opportunity Fund I, both anchored by Xylem, to further support high-growth water startups. The timing couldnt be better. Both VC and entrepreneurial attention are shifting toward climate adaptation and resilience, and water is at the center of that transformation. Institutional agility is possible Ive seen too many large companies fail at innovation simply because they lack the structure and discipline to integrate external ideas. But Xylem Innovation Labs is proof that it doesnt have to be this way. I believe that when a corporation commits to engaging with startups strategicallyrather than treating innovation as a PR stuntit can create an engine for sustained competitive advantage. Xylem has done this by taking external innovation seriously, embedding it into its core strategy, and executing it with speed and transparency. In todays world, where water challenges are intensifying, integrating emerging technologies isnt optional, its a necessity for survival and long-term growth. Tom Ferguson is founder and managing partner of Burnt Island Ventures.
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E-Commerce
The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. In most companies, generative AI is full of contradictions. On one hand, 67% of business leaders predict that GenAI will transform their organization in 2025, according to a KPMG survey. On the other, just 36% of executives say their company has a well-defined vision for AI. The core issue: Nearly 2.5 years after ChatGPTs introduction, most companies are still stuck in what I call prototype purgatory. Theyve bought and attempted to adopt off-the-shelf GenAI tools and developed pet project prototypes. But despite big promises from vendors or demos, theyve generated little more than incremental valuefar from the AI revolution that was promised. I see this constantly when talking to enterprise execs. Theyre frustrated. And the data bears this out, too. Recently at A.Team, we surveyed 250 senior tech leaders responsible for AI initiatives at their companies and found that only 36% of organizations have successfully deployed AI to production. (The majority of respondents came from enterprise companies.) The rest remain caught in an endless cycle of proof of concept projects and pilotsor havent gotten started at all. Its not hard to see why this is happening. The space is moving at whiplash speed, disrupting itself weekly. Its impossible to upskill your full-time employees on all things AI, which makes it difficult to make crucial technical decisions. At this stage of the game, locking into one platform is highly premature. But amidst these struggles, some companies are breaking through. The most fascinating part of our research was what AI leaders do differently than AI laggardsand it’s not what you might expect. The talent equation: Blended teams win The most striking finding from our research was that organizations that use blended teamsa model that integrates specialized freelance talent with full-time employeesare twice as likely to reach advanced stages of AI innovation. These companies find that this model helps alleviate the AI talent crisis that most companies are experiencing. Ninety-four percent of the tech leaders we surveyed said talent constraints are their primary barrier to innovation, with 85% having delayed critical AI initiatives due to talent shortages. [Graphic: A.Team 2025 State of AI Innovation Report] Theyre finding that traditional hiring can’t solve this problem89% said the traditional recruitment model is broken. Two-thirds of respondents said it takes at least 4 months to hire top engineering talent. These protracted hiring cycles are particularly problematic in AI development, where technology evolves at a breakneck pacerendering traditional workforce planning obsolete as new possibilities emerge and roadmaps change. In 2025, its hard to know the exact skills you will need in six months. Successful organizations that have escaped prototype purgatory have found a different approach with blended teams, and they report stunning improvements from incorporating freelance or fractional talent into their teams: 99% enhanced innovation capability 98% improved project success rates 96% accelerated speed of delivery [Graphic: A.Team 2025 State of AI Innovation Report] Build versus buy: A third way may be the answer For the past 2.5 years, Ive watched build vs. buy become one of the dominant discussions in executive boardrooms. While off-the-shelf AI tools like ChatGPT Enterprise and GitHub Copilot deliver obvious value, it now looks like the build approach is winning. Among companies that have successfully deployed AI to production, 93% say building custom solutions delivers more value than off-the-shelf tools. But that might not be the whole story. The most successful organizations aren’t building everything from scratch, however. They’re taking an “assemble” approachleveraging the explosion of open-source building blocks (we’ve seen a 60% boom in open-source GenAI contributions on GitHub in the past year alone) while customizing solutions for their specific needs. The assemble model is built for speed; integrated components can be easily updated or swapped out, which is crucial when the shelf life for state of the art AI is shorter than a jar of organic marinara sauce. It allows you to keep the most crucial part in place: developing these GenAI components into existing workflows that empower your employees and customers, giving you a true data moat. When you look at where the senior tech leaders in our study are making their investments, it reflects this kind of foundational approach: 50% are increasing spending on AI safety and monitoring tools 49% are prioritizing AI development platforms 41% are investing in data infrastructure [Graphic: A.Team 2025 State of AI Innovation Report] Theyre not investing in the models themselves but in everything needed to turn them into production-grade systems: data pipelines, testing frameworks, monitoring tools, and integration capabilities. Want ROI? Start with AI-powered automation One of the biggest questions about generative AI is: Are companies seeing ROI? And if so, where? We got the answer by asking AI leaders their expected ROI timeline across four key areas of focus: Custom AI product development AI-powered automation Customer-facing AI features Internal AI tools [Graphic: A.Team 2025 State of AI Innovation Report] Not surprisingly, AI-powered automation had the highest ROI rate already achieved, at 14%. Surprisingly, customer AI product development came in second, at 12%. Perhaps most surprisingly, most leaders expect to see ROI across every use case this year. [Graphic: A.Team 2025 State of AI Innovation Report] Our research suggests that a significant portion of that investment will go into custom AI product development and customer-facing AI features. While the dominant AI discussion has focused on cost cutting, more respondents said they were focusing on generating ROI through revenue generation (46%) over cost cutting (30%). [Graphic: A.Team 2025 State of AI Innovation Report] Its been said a million times, but it bears repeating: This will be a critical year for AI development inside most companies, with many Fortune 500 players at risk of falling behind. And while there have been whispers of a trough of disillusionment, tech leaders remain bullish: 96% plan to increase AI investments in 2025, with over half planning increases of 51% or more. The challenge isn’t a lack of ambitionit’s execution. Most AI initiatives fail at the last milenot because the technology isn’t viable but because organizations underestimate the complexity of productizing AI and dont have the right talent with the right mindset inside their organization. Companies that embrace these challenges and think differently will escape prototype purgatory. The rest may find themselves in limbo for years to come. Raphael Ouzan is cofounder and CEO of A.Team.
Category:
E-Commerce
The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. AI is no longer a side project. It now sits at the heart of how companies grow, compete, and make decisions. Yet many leaders still struggle to separate hype from value and wonder how to invest wisely without wasting time or resources. A key challenge lies at the top: a lack of AI literacy among executive teams. Research covering nearly 7,000 executives across 645 firms shows a clear pattern: Companies led by AI-literate teams are more likely to identify where AI can create value and act on it. Rethink responsibility Many executive teams still treat AI as a tech issuesomething for IT or data teams to figure out. But AI is a leadership issue. It belongs on the agenda of every CMO, CFO, CHRO, and CEO. More importantly, its not about a single role. Its about the collective literacy of the top team. Research rooted in upper echelons theory confirms this: AI-literate leadership teams are more likely to build strategic visions that integrate AI and translate that vision into tangible action, from capability building to execution. So appointing a chief AI officer (CAIO) without a broader shift in understanding wont be enough if the rest of the executive team cant grasp the art of the possible and actively shape the direction AI takes in the business. As one leader put it, Hiring a CAIO is like hiring a pilot for a crew that doesnt believe in flying. The cost of poor AI literacy As MIT Sloan Management Review points out, The overall low literacy rate is a problem for todays executives, who will face more and more processes or products that claim to be powered by AI. Making informed decisions about these AI tools requires leaders to understand how they align with strategy and operationsand to know which questions matter. Without a clear understanding of what AI can door where it breaks downexecutive teams fall into familiar traps: Buying into hype they cant evaluate Investing in tools without understanding their fit Setting expectations AI (or teams) cant meet Focusing on flashy pilots instead of long-term capability building The result is often pilot purgatory, or initiatives that stall. Missed opportunities. And in some cases, the slow decline of companies that once dismissed digital as a passing trend. From confusion to competence: The AI literacy ladder To help executive teams assess where they stand and what to do next, we use a five-step model: the AI literacy ladder. Think of it as a five-step staircase representing the typical journey executive teams take as they build fluency in AI, moving from scattered perspectives to a shared understanding and strategic alignment: Confusion: AI feels like a buzzword. Theres no shared understanding or agreement on relevance. Curiosity: Interest is rising, but views are fragmented. Theres little clarity on where to begin. Comprehension: The team develops a common language around AIs potential and risks. Confidence: Teams ask sharper questions and align on use cases that matter. Competence: AI becomes part of strategic planning and decision making. [Graphic: Philippe De Ridder, CEO at BOI] Why AI-literate teams outperform When executive teams build AI fluency together, they unlock a dynamic we call the AI fluency flywheel: Teams that move beyond confusion and start learning together gain momentum. They stop treating AI as an isolated initiative and start treating it as a core strategic capability. Over time, this fluency allows them not just to respond, but to lead. [Graphic: Philippe De Ridder, CEO at BOI] So where do executive teams learn AI? Despite the flood of AI training programs, few are built for leadership teams. Most are either too technical, too long, or designed for individuals. Whats missing is a shared learning experience. One that helps leadership teams: Understand whats possible and whats not Cut through noise and inflated promises Align on use cases worth pursuing Build a common language across roles Closing the gap starts at the top As AI reshapes how organizations operate and compete, executive teams cant afford to stay on the sidelines. The journey toward AI maturity isnt about becoming technical experts. Its about building shared fluency across the leaership team. It starts with honest reflection: Where are we on the AI literacy ladder? What will it take to move forward, together? The first step is simple but powerful: Make space for the conversation. Invite different perspectives. Commit to learning together. Teams that do this wont just keep up. Theyll help shape whats next. Philippe De Ridder is founder and CEO of BOI (Board of Innovation) and AUTONOMOUS. Laura Stevens, PhD is managing director, Data & AI at BOI.
Category:
E-Commerce
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