Strengthening Foresight Strategies

A strong steel chain link.

Rohrbeck literally wrote the textbook on corporate foresight. Just this past year, he conducted a global benchmarking study focused on institutionalizing strategic foresights. The FEI25 community committee gathered around a virtual roundtable to ask diverse questions about how organizations can action and gain true value from corporate foresights.

Adapting to Uncertainty

Su-Feng Kuo: What is it about corporate foresight that is so tough to implement?

Rene Rohrbeck: When we first looked at this, we were in an industry which wasn’t a particular situation which needed to reinvent itself. My research started when I was in telecommunications, which is hardly known as telecommunications anymore because it is something else. It is connectivity. It is IT. It is AI. So we were at a particular spot, saying, how can we reinvent our position in the value chain, our business model? And then you realize that if you want to have a conversation with other organizations, which is what we did, we went into a lot of benchmarking, but there were not so many out there who said, yes, that happened to us last year as well.

Now one can call it foresight, but it’s probably not foresight on my side. It just happens to be the case that now we find more and more companies which find themselves in the position that they deeply need to reinvent themselves. Where does innovation lead us? What is the strategic angle to it? How can we bring a joint narrative for our organization into existence, which guides us towards a new type of innovation, a new type of economy, etc. For us, it was at the start, something which we needed, and we were looking for guidance. We built a maturity model and then bit by bit, we built a consultancy practice around it. We built a curriculum about it, and now we are probably among those voices who can help you institutionalize this corporate foresight muscle in your organization.

The Art of Foresight

Kuo: In Rene’s first book, he reviewed a few cases and talks about why companies didn’t really take the opportunities at that time to innovate. That really struck me. People are not comfortable with change. They are more comfortable to do what they are doing right now. So how can we make people aware of the importance to see the opportunities for growth and how they change that mindset? How can we help them start the first step and feel supported or comfortable with that uncertainty?

Rohrbeck: It’s often also a kind of scapegoat debate, where, middle management would be saying, but we don’t have the top management support. Top management is saying, well, I better look outside because my middle management is really not bringing up new things. We need to create this catalytic moment. And, how that often happens is by a program which we announce, OK, we want to understand what’s the next generation intel. What’s the next generation of our company?

We want people to get involved. So this catalytic moment can come from a larger program. It can also come from joint foresight. We’ve been recently working with a big chemical company over 500 years of age, which said, our industry is changing so dramatically, and also how is our workforce thinking about the future of our company. We need to bring them together. What we did is actually, a big scenario program, which started in the middle, went to the top, and then cascaded down the organization to focus people around joint narratives. It’s really this capacity to build narratives which bring together many people, which invite many people to contribute, and then also to execute on new strategy, which is the core, if not sort of the heart of the craft, the design, and the art of foresight.

Catching the Right Wave

Kuo: I feel like my company and my team are going through that transformation. Because the environment is changing so dramatically, and now we have a new strategy, for growth to 2030. But I think the company has done a lot of communication on where we are going. But I feel like it really takes a village, and it takes so much time. Do you have any strategy to make sure that people have changed their mindset, they really put the best into their work? Because I feel like from time to time, you still hear the doubt, is this really where we’re going? How do you deal with that?

Rohrbeck: I think most companies, they realize that we’re also in a change from an old era to a new era. I often compare it to sport because I like to do a lot of different sports, and I’m getting quite excited about new sports all the time. When I was young, I was rowing, and I liked rowing. This sense of being on the team, in the boat with eight people, we’re all rowing and maybe we’re a bit faster than the others, then it’s really good. If you’re a bit slower, then it’s less good. But you know what you do. You are in a boat. You’re often with very sophisticated equipment, and you’re feeling in sync with everyone else. You know that everyone has been training for this.

Years later, I got into surfing, which is a total mess. You might be pedaling out there and every wave hits you and you’re not having a good time. I think what’s what we see in many companies today is this realization that while we need to spend 80% of our time to still be able to row and basically row faster than the other rowing boats, which have exactly the same boat and also motivated people who know what they’re doing.

But we’re starting to be in a situation where it’s maybe 20% that we need to get into surfing. We need to understand when will the next waves come? What are the patterns in this industry? What are the sets in which a surfer knows a different pattern of waves which are coming in? Then you need to be getting ready. You need to acquire new capabilities before other companies. And then this happens all in a moment. There comes this moment where you realize, if I’m now waiting to see that the market is either developing or not developing, then it will develop without me. So there’s this moment where you need to go all in.

Foresight as Your Superpower

Kara Cunzeman: I often see as a foresight practitioner, the word foresight, strategic foresight, people get scared. There are actually studies done on people that don’t like the word strategy, and we have two scary words. So maybe step back and just in the simplest form, kind of describe what strategic foresight means to you, and then make the case to the innovators in the room. Why is it so essential that we tie those? I’d also love to hear your take on how you communicate this to non-foresight practitioners.

Rohrbeck: I think the general idea people need to get is that you want to go where the ball will be played next. Think of Wayne Gretzky, the ice hockey player. You would often see him skating off to a different part of the field where the puck was not, visibly, and you were wondering if he wants to have a break or if he wants to grab a coffee. But he kind of saw the pattern happening. He was understanding, where will this move?

It was often periods of 30 years where things are pretty stable in an industry until drastic changes happen. As foresight experts, we also know the K-waves, which have been kind of mapped out in 50, 60-year patterns. In a way you could get this feeling that as an organization, maybe I need foresight only every 30 years. That is, however, right now probably not true for any industry because AI is changing fundamentally how we think about intelligence, employability, how we make decisions, how we plan, how we innovate, and so on. This notion of having to take one or maybe even two steps back and look at how is this evolving? What is the end game in this? What happens if we add more and more compute? What can we do in innovation, which we couldn’t do before with a bunch of motivated people from different backgrounds. This is where foresight suddenly opens a new universe.

I should have told you this at the start, but warning, you’ve been infested with the foresight virus, and it will never leave your body again. Because you suddenly look at the world differently. You think in systems. You think about how things will evolve in the mid and long term. And that also means that you’re not satisfied anymore by just fixing something in the short term.

But it also gives you this kind of superpower. It’s ultimately a set of tools and techniques on how to think differently, how to think in systems, and to map out with yourself and with others an exciting path forward. That’s what everyone who has sort of been in touch with this, ten years later, they will tell you, this changed sort of my perception on what I was doing before in innovation.

Editor’s Note: Click here to view the full video of the conversation between the innovation community and Professor Rohrbeck, where they discuss topics such as AI, foresight tools and how to measure success. The video begins with a short session on “Aligning Innovation Business Strategy,” featuring Mike Hatrick, Vice President IP Strategy & Portfolio, Volvo Group; and concludes with a question-and-answer session.

Positioning Quantum Technology for Future Innovation

Futuristic wormhole with beams of light streaming out.

Growing Quantum Capabilities

Quantum mechanics, the theory underlying quantum technology, emerged in the early 20th century. However, it wasn’t until the late 20th century that the potential for quantum computing began to be explored.

Four Areas of Quantum:

  • Quantum Computing: Leveraging quantum phenomena to perform complex calculations beyond the capabilities of classical computers. This holds the potential to revolutionize fields like drug discovery, materials science, and artificial intelligence.
  • Quantum Security: Utilizing quantum mechanics to develop secure communication networks and protect sensitive data from increasingly sophisticated cyber threats.
  • Quantum Networking: Creating networks that rely on quantum phenomena to transmit information with unparalleled security and efficiency.
  • Quantum Sensing: Harnessing the sensitivity of quantum systems to develop highly accurate sensors for applications in healthcare, environmental monitoring, and navigation.

The sensing capability stands out as a particularly promising area with near-term applications. Sensors can offer precision with early disease detection, enhanced navigation and improved environmental monitoring. The quantum sensing market is projected to reach $1.3 billion by 2028, with a CAGR of 13.4%, according to Global Market Insights.

Take the Quantum Leap

During the third day of FEI 2025, Leslie Shannon, Head of Trend and Innovation Scouting at Nokia, will give the keynote presentation, “Unpacking Quantum For Innovation and Your Organization.” Quantum technology, while seemingly futuristic, is rapidly approaching mainstream adoption. This session demystifies the quantum landscape, providing a foundational understanding of its potential impact on innovation and business strategy.

The session will examine a brief history of quantum mechanics, and how today we stand on the cusp of a quantum revolution, with significant advancements being made across various quantum domains. This includes quantum computing, security, networking and sensing capabilities. Quantum sensing stands out as a particularly promising area with near-term applications.

This session further provides attendees with an understanding of the current state of quantum technology; insights into the four key areas of quantum and their potential applications; a deep dive into the promise of quantum sensing; and strategies for preparing for the quantum era and incorporating quantum technologies into their organizations. Join us to explore the fascinating world of quantum technology and discover how it can drive innovation and transform your organization.

FEI 2025 will be held May 19-21, 2025, Omni Boston Hotel at the Seaport Boston. Click here for more registration information.

The Promise of Quantum Technology

Quantum technology could create value worth trillions of dollars within the next decade, according to McKinsey & Company. While some categories are in the early phases, research and development of this growing field shows substantial promise.

In McKinsey’s third annual Quantum Technology Monitor, the company synthesizes the latest opportunities in this burgeoning field. In the article accompanying the report, “Steady progress in approaching the quantum advantage,” McKinsey notes that four sectors—chemicals, life sciences, finance, and mobility—are likely to see the earliest impact from quantum computing and could gain up to $2 trillion by 2035.

Investments in the public and private sectors are increasing. Talent development, the consulting company notes, is also growing while countries need to “focus on broad collaborations to build strong capabilities” in quantum as the field progresses. This means that academic hubs, government support, entrepreneurship, and industry partnerships should all play a role in future growth—and the impact on the innovation community could be substantial. “Developing and scaling such regional innovation ecosystems (including research consortiums) will be a determining factor for achieving wide adoption and commercialization of quantum technology,” observes McKinsey.

Video courtesy of Massachusetts Institute of Technology (MIT)

The Rise of Corporate AI: Building the Foundation for Innovation

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Rewiring the Bottom-Line Impact of AI

Overall, AI usage in large corporations is gaining momentum. According to a global survey from McKinsey & Company, “The state of AI: How organizations are rewiring to capture value,” more than three-quarters of respondents now say that their organizations use AI in at least one business function. McKinsey notes that companies with at least $500 million in annual revenue are changing more quickly than smaller organizations. These leading companies are deploying generative AI, redesigning workflows, putting senior leaders into roles to oversee AI governance and hiring for new AI related roles.

Other survey results from McKinsey include:

  • 28% of respondents whose organizations use AI report that their CEO is responsible for overseeing AI governance, though the share is smaller at larger organizations with $500 million or more in annual revenues, and 17% say AI governance is overseen by their board of directors.
  • 21% of respondents reporting gen AI use by their organizations say their organizations have fundamentally redesigned at least some workflows.
  • The survey findings also shed light on how organizations are structuring their AI deployment efforts. Some essential elements for deploying AI tend to be fully or partially centralized. For risk and compliance, as well as data governance, organizations often use a fully centralized model such as a center of excellence. For tech talent and adoption of AI solutions, on the other hand, respondents most often report using a hybrid or partially centralized model.
  • 27% of respondents whose organizations use gen AI say that employees review all content created by gen AI before it is used. A similar share says that 20% or less of gen-AI-produced content is checked before use.
  • Many organizations are ramping up their efforts to mitigate gen-AI-related risks. Respondents are more likely than in early 2024 to say their organizations are actively managing risks related to inaccuracy, cybersecurity, and intellectual property infringement.
  • Only 1% of company executives describe their gen AI rollouts as “mature.” Even though these remain early days for deployment, we are beginning to see the impact when these practices are employed to capture value.
  • In the latest survey, 78% of respondents say their organizations use AI in at least one business function, up from 72% in early 2024 and 55% a year earlier.

Uncovering Organizational AI

During FEI 2025, Rick Robinson, VP, AgeTech Collaborative, VP Product Innovation at AARP, along with Shahid Azim, CEO, Managing Partner, Co-Founder at C10 Labs, and Sanji Fernando, Operating Partner, Data & Artificial Intelligence at Frazier Healthcare Partners, will hold a keynote, “No-Hype AI Impact on Organizational Efficiency, Value, Teams & The Bottom-Line.”

There can’t be more noise around organizational use of AI. It will surpass expectations, it will fall short of promises, we don’t even know what it will do!!!! Each of those distinct perspectives are simultaneously being voiced by smart people. With thought leaders that have already proven success, we stop the madness with a no-hype, in-the-moment conversation on what is real and what you can do now for your organization. As a community, we then collectively uncover use cases and case studies showcasing the real-time “AI Impact on Organizational Efficiency, Value, Teams & The Bottom-Line.”

FEI 2025 will be held May 19-21, 2025, Omni Boston Hotel at the Seaport Boston. Click here for more registration information.

Managing the Implementation of Generative AI

It seems pretty clear, according to comprehensive surveys such as the one from McKinsey, that AI use will continue to climb at both large and small organizations. Experimentation, testing and deployment will continue to ramp up, and the scale will depend on each firm’s capabilities, and whether it’s a centralized, decentralized or hybrid model. New hires, new skills and new training will be needed for this AI-enabled workforce.

As McKinsey reminds us, despite the hype, it’s still the early days of this movement. McKinsey concludes, “Use continues to surge, but from a value capture standpoint, these are still early days—few are experiencing meaningful bottom-line impacts. Larger companies are doing more organizationally to help realize that value. They invest more heavily in AI talent. They mitigate more gen-AI-related risks. We have seen organizations move since early last year, and the technology also continues to evolve, with a view toward agentic AI as the next frontier for AI innovation.”

Video courtesy of Bernard Marr

Practicing Innovation in the AI Age, Part 2

Futuristic image streams of lasers/light beams rushing into the distance.

Focus on the Front End of Innovation

What is up for debate right now in the innovation space? Despite the focus on technology like AI, for food and beverage innovation veteran Zeinab Ali, who recently retired after a career in senior research and development roles with brands like Campbell Soup Company, PepsiCo and Nabisco, it still comes down to the simplicity of knowing the consumer.

“The challenging piece that I see is more one of resources—the lack of resources. People don’t have the bandwidth to do a lot of things that they would love to do,” says Ali. “It’s the background work that really fuels innovation because people need a safe space and given the freedom to play. I think that we’re losing that. When the initiative or project arrives, with very little notice, we end up starting from scratch. There was no forethought, which makes it very challenging. Where does most of the shortcuts take place? In my experience, it’s the front end of innovation.”

She continues, “Let’s say the project was a one-year project. You skip the front end of innovation. You start failing with the consumer testing. Redo the concept many times. And by the time you launch the project, it is two years long. If you did the front end right, you could have made that project one year. The concept should be worked and cemented at the front end. Does the consumer want or need this? Can we make it? Can we make money? All those three questions should be answered upfront. My best practice advice is to spend as much time as possible on the front end because then from front end to the launch, it’s really a straight line.”

As for AI, Ali has mixed emotions. Certainly, as a tool we should embrace it. But just don’t get too lost in the algorithms. Again, focus on the consumer.

Ali observes, “I see reliance on technology, whether it be AI and social media more than actually connecting with the end user. What’s disappearing is the connection with the end user of your product because we’re relying on the algorithm. Yes, use it, but don’t use it instead of the consumer. Technology is supplemental, not the other way around. Because within the corporation, we drink our own Kool Aid. We get excited about what we offer. We get excited about the technologies that we deliver. We get excited about it because we have a patent. But I think the human factor will keep you humble and keep you focused and make you deliver the project on time with less costs because you’re not adding things that they don’t want. Don’t take the consumer focus away from innovators.”

Innovating on Process

Still, not everything about AI and technology should be feared. It just depends on your perspective, especially as it relates to process and the future development of your customer base.

Emil Georgiev, Vice President – Customer Experience Design, IKS Health, relates, “AI has changed the game of innovation in a very significant way because it has altered the way that a lot of the processes, optimizations, and workflows are happening. AI gives the base of the autonomous software that does everything on its own with very little or no human intervention. It changes in a significant way how people are interacting with your product or service. That necessitates rethinking of your whole philosophy of how you serve those customers. It creates a significant set of opportunities for process optimization, for being able to utilize information in new and novel ways that have not been used before. In that way, it improves all the operations, and improves the capacity of customers to understand what is going on.”

In healthcare, as Georgiev notes, it’s a technology that is influencing how patients interact with corporations, and how corporations interact with patients and other clients.

“With the ability to collect and process enormous amounts of information, it improves processes, improves analytics, the understanding of what is going on, and gives customers new levels to fine tune their operations. For us as vendors, for those customers, the customers being healthcare clinics, hospitals, and so on, we must make sure that we are at the cutting edge of what AI and machine learning can offer in order to make sure that these capabilities are built into what we offer as well,” says Georgiev.

The cost factor should not be overlooked when it comes to how AI can streamline the process.

Georgiev notes, “AI has done a significant level of innovation with respect to the overall cost of the services that we can deliver nowadays. Because more and more, this automation takes place in a way that removes cumbersome, costly and time sensitive processes that were done by people before. Not with very high level of accuracy. So the level of accuracy has increased. The productivity has significantly increased, but it changes some of the processes as well. Now we’re not talking about the AI innovating for you yet, but it seems like we are getting there. It is not a question of whether you utilize it, but how effectively you utilize it to stay competitive.”

What do you see on the horizon for innovation, especially in the context of AI’s influence?

Georgiev says, “Notwithstanding the emergence of AI that can make connections smarter than the human being, which I don’t want to explore at this point as a venue, but it may be coming. The advent of AI significantly enhances what a human being can do. For right now, I choose to at least look at this as a significant enhancement. Part of the future is to use the same innovation approaches that we have but building as many AI/ML enhancements along the way that we can envision. That becomes basically a way for us to innovate faster and innovate cheaper.”

There may be a level of foresight, Georgiev suggests, that AI can play a larger role in developing: “AI can enable you to conduct simulations faster, be able to anticipate what is coming, do projections, etc. I see a lot of work being done in development, this type of simulation model and the ability to use enhanced analytics to predict the future with a certain level of success. That gives you directional focus on where innovation should be focused going forward to a very significant degree if used correctly.”

“Innovation is something that happens, but it has to be directed. At least, in a private enterprise, it has to be directed in a way that aligns with the company’s vision and also with where those contributions are going to be most significant in terms of changing the life of our customers or their patients,” he says.

Coaching the Future of Innovation

Lisa Costello, Director and Head of Platform, Prologis Ventures, sees AI from a different lens, perhaps, than other innovation professionals.

“As I work in the venture capital environment, we can see that AI is often being overvalued by investors compared to the outcomes that it produces. That’s an unfortunate truth that we’re all going to realize in the next couple of years as we see these high valuations become more realistic,” says Costello.

“That said,” Costello continues, “AI is changing the game for every business, as it helps take a lot of the busy work out of what used to be required for innovation. Whether it’s analyzing large datasets or research that you would have normally had to sift through, or even analyzing large amounts of sentiment data to better understand how people feel or look at the world around them. If you can make sense of all that data more quickly, then you can get to insights a lot faster. Is it the disruptive technology that people say it is? Is it going to displace people? I think it’s too soon to tell how big the impact will be. But right now, we are seeing individuals spending time on more valuable activities like strategy and implementing ideas.”

She adds, “The mistake I’m seeing some organizations make is just telling individuals to ‘go use AI’. But this is limiting. At the end of the day, AI is a tool, just like any other technology. You have to start with the business problem – the sticking point or friction area – and then use AI to solve it.”

Apart from AI, Costello sees other shifting trends that have impacted innovation, and hence, innovation best practices. One aspect is the structure of the innovation team.

“There’s been a long-standing debate about whether innovation teams should sit within the core organization, under its direct oversight, or operate more independently to allow ideas to flourish. Both approaches have pros and cons, but in my experience, there’s real value in staying close to the core business,” says Costello.

“You get access to customers, insight into what the core business prioritizes, and the opportunity to consistently show value. This is critical for innovation teams, especially when budgets tighten. Because being close to the company not only helps demonstrate impact on business outcomes but also enables more frequent communication and alignment with senior executives, which is what keeps these teams supported and thriving,” she says.

Getting Close to Customers

“When it comes to thinking about the long-term sustainability of our business, continuing to drive value and revenue for the company comes in a lot of different forms, and it doesn’t require these fancy innovation labs or even big budgets,” observes Costello. “It can work within the constraints of the organization and actually use those constraints to fuel bigger ideas because you’re so close to the end customer and to what their challenges are.”

The future seems bright for innovation, with AI there to help support the generation of ideas and the broadening of innovation to all parts of the organization.

Costello adds, “AI can help individuals at different levels of the organization work through their ideas in a new way. There are associates who might have great ideas because they’re so close to the problem and to customers. If you can use AI to empower them and coach them through developing those ideas, then they should be able to implement more of them. All of your ideas can’t come from the top down or you’re going to be missing out on a lot of opportunities.”

“Budgets get controlled around a boardroom table, but the best ideas aren’t usually formed there. They start on the floor with your customers,” she says.

Editor’s Note: This is part 2 of a two-part blog on innovation best practices. Part 1 looked at AI and creative velocity, while part 2 examined AI, the front end of innovation and more.

Video courtesy of R&D Today

Practicing Innovation in the AI Age

Futuristic fractal sphere with digital egg emerging in the center.

AI as Thinking Partner

So just what might the future hold for the corporate innovator? For Prapti Jha, Innovation Strategist, We Speak Innovation, she sees AI as having a broad influence. In some ways, this is about communicating innovation more easily and effectively to others. Can anyone now be an innovator?

Jha observes, “One of the biggest shifts that I see coming is because of this generative AI boom, we all can learn something about a field that was totally a black box for us. And innovation is a part of it. People from other fields can also learn a little bit about innovation easily, pretty much as compared to the time it would take them earlier. The same goes for the innovators for other fields like manufacturing or any other field that might feel like a closed box to us.”

“We all have that access to information in a much more digestible way,” says Jha. “This leads eventually to a world, a corporate setting, where we’ll have an intra-collaborative, interdisciplinary setting—basically all the different disciplines working together. This is something that innovators have always pushed towards to break the silos of the corporate world. But I see it happening even more with AI. This is happening in other fields as well, such as coding, where other people can now jump into that field and create that output.”

Surely, the discipline of innovation is more complex than just coding yet Jha makes the point that AI is flattening the landscape, and making it more accessible for all.

Jha says, “That leads us to the future, where there will be more interdisciplinary kinds of organizations. All of these functions will be more connected to each other and also at times overlapping with each other. I’m very curious to see how this would lead to actual change in organizational structures.”

“Because as innovators, we also work in the area of development and design. What would that 2030 design might look like with AI being such a huge player into our teams? Basically, AI is moving forward as a colleague that we have, and it’s making all of us much more capable of understanding something that would be hard for us to digest earlier. Again, things are moving so fast. Of course, next year, I might have more ideas about it or a different idea. But that’s what I’m thinking right now,” says Jha.

Jha brings up an interesting point of AI as a thinking partner. This could be key when exploring all of the AI solutions for innovation that are now developing in the marketplace.

Jha continues, “We need to capture the idea of how AI can be your thinking partner. How you think as a human and how can you leverage AI solutions or AI as a thinking partner is something of a mindset that we must develop. Once we have that mindset of leveraging AI for whenever we are doing a thinking job, and, of course, then also comes tangible jobs that we give AI to do for us. That gives us an opportunity to embrace all the different solutions. But that mindset, that approach, would still stay intact for a while, and that’s something that is important for us to understand and rewire our brains rather than just jumping into the solutions. If we have that approach, that mindset, that really helps us filter the things that we need and then look out for the solutions that are beneficial.”

Moving Ahead with Creative Velocity

For Leslie Grandy, Lead Executive in Residence, University of Washington – Michael G. Foster School of Business, “Generative AI can be crucial in helping overcome biases like Expert Think and organizational inertia. By possessing psychological distance from the problem and providing alternative perspectives and solutions that may not be influenced by human biases or traditional industry norms, generative AI can challenge teams to consider truly novel approaches to solving problems.”

Grandy, who is the author of Creative Velocity: Propelling Breakthrough Ideas in the Age of Generative AI, feels that AI can help teams with a wide range of collaborative tasks and creative skills.

“Any team—not just a team tasked with innovation—can partner with Generative AI through structured creative frameworks that help develop collaboration and creative thinking skills,” she says. “This means innovation can come from any role or level in an organization. Incorporating generative AI into the team’s creative processes can enhance their problem-solving abilities, accelerate innovation, and more effectively address complex customer needs. However, it’s important to view generative AI as a tool to augment human creativity rather than replace it. The most effective approach combines the analytical power and extensive knowledge base of generative AI with the nuanced understanding, empathy, and creative intuition of human product teams.”

As for what may be on the horizon, Grandy, feels it will still take a while to sort out the ethical issues and actual jobs that AI might reduce. Until then innovation awaits in any number of fields.

“I am fascinated by the conversation around artificial general intelligence,” relates Grandy. “I think this is what many people fear will be the engine for reducing enterprise human capital. It’s probably more than a decade off from realization, and it will likely take longer to sort out the ethical issues around its applications.”

She adds, “I also expect to see rapid growth in the use of digital twins across various industries, ranging from healthcare to building design and management. These ‘living models’ of complex systems can enhance everything from positive patient outcomes to building performance. Mixed-reality experiences will become more mainstream for the enterprise. While the metaverse garnered attention in popular culture, enterprise adoption of XR for training, remote collaboration, and simulations will accelerate. Penetration across verticals like consumer real estate and entertainment, along with hospitality, food services, and manufacturing, will continue to grow.”

Editor’s Note: Join us next week for part 2 of this blog, as we conclude our innovation best practices series.

Video courtesy of Plug and Play Tech Center

FEI25 Names Finalists for Collective Intelligence Startup Competition

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New Videos: Review the FEI25 Collective Intelligence Startup Competition Finalists

Introducing The Collective Intelligence Startup Competition Finalists

Accelidea, www.accelidea.com

Accelidea is a multi-agent AI platform that automates up to 80% of the regulatory, quality, and engineering workflows required to bring a medical device to market. Today, a typical Class II device takes 3.5 years to reach market, involving 16+ functional roles and over 5,000 handoffs. Even the most experienced teams are buried in fragmented tools, siloed processes, and repetitive manual documentation. These delays cost companies millions and most importantly, delay life-saving technologies from reaching patients. Unlike traditional tools, we’re not just digitizing forms. We’re building a system that thinks, flags gaps, and accelerates iteration. It’s the revolutionizing infrastructure layer for smarter, safer, faster medical innovation.

Ada IQ, www.adaiq.com

At Ada IQ, we’re reimagining how consumer products are designed. Our AI platform blends human intelligence with deep data to help companies move from idea to validated product concepts—faster and with greater confidence. We specialize in the front-end of product development.

Our platform captures and interprets human inputs—like sketches, feedback, trends, and market signals—and turns them into product concepts that are both creative and practical. It’s like giving every design team a strategic co-pilot: one that sees hidden patterns, connects the dots, and surfaces ideas worth pursuing.

Ada IQ is for teams who want to design smarter, faster, and with the consumer in mind from day one. This is product innovation—supercharged by AI and guided by human creativity.

Caid, https://www.linkedin.com/company/ca-id

At Caid, we’re redefining how digital meets the physical. Our AI tool transforms natural language into precise, adaptable computer-aided designs—enabling quick physical prototyping for industries, maker-spaces, and research and development laboratories. Conventional CAD tools can be laborious and time-intensive, frequently resulting in users having only a faint idea of their design. Caid fills that void by utilizing distinct human tacit knowledge and merging it with advanced machine intelligence, unleashing the potential of collaborative intelligence.

At the heart of our mission is the belief that human experience, intuition, and creativity—when collaborating with Caid—can achieve results neither could alone. Join us in reshaping the physical design landscape to anyone, anywhere.

Coworked, https://coworked.ai

Coworked is transforming project management by pioneering AI solutions that empower teams to achieve more with less effort. Our flagship product, Harmony, is the most comprehensive AI Project Manager coworker designed to take on PM tasks, enabling project managers to focus on strategic leadership and innovation. Built on a proprietary agentic AI framework, Harmony integrates seamlessly with popular project management and communication tools, operating as an autonomous team member. With a mission to make enterprise change as seamless as day-to-day operations, Coworked is dedicated to enhancing project efficiency, reducing costs, and helping organizations realize the full potential of their project management capabilities.

Gigabug Computer, https://gigabug.org

We research and develop novel physics-based computer architectures to address the ever-increasing energy demand for AI workloads. We aim to have the first commercially available integrated circuit to accelerate adoption and push algorithm development for this emerging technology. Our product is an AI accelerator that can easily interface with modern classical computers, offering an ultra-low-power drop-in replacement. By utilizing physics as a natural compute resource, we can unlock several orders of magnitude improvements in energy consumption and runtime over classical digital processors (CPUs/GPUs/FPGAs). Our device will target combinatorial optimization and generative machine learning problems, which are at the forefront of all major commercial industries.

Kathalyst, https://www.kathalyst.ai

Kathalyst is an AI-powered platform that eliminates the biggest barrier to modernization—understanding legacy systems. Our technology automates documentation, system visualization, and semantic code conversion, giving companies a clear roadmap to transition away from outdated software. Instead of relying on expensive consultants or risky, manual rewrites, enterprises can now reduce costs, mitigate risks, and confidently upgrade to modern technology with a structured, automated approach. By making legacy software modernization faster, more reliable, and scalable, Kathalyst is redefining how enterprises future-proof their technology.

Neoclease, https://www.neoclease.ai/

Neoclease builds new nucleases as genetic medicines, each individually designed to target a specific gene. Our differentiated approach is enabled by our generative AI model and evaluation pipeline, trained on millions of known nucleases, overcoming today’s barriers to gene editing. We engineer safer, more precise, and efficient genetic medicines. We’re currently validating our first nucleases for Parkinson’s disease with an approach that could be the first therapeutic to slow or fully halt progression of the disease.

Neoclease’s platform is scalable across multiple diseases, creating a new class of gene editors tailored for precise, disease-specific interventions. Our AI-driven pipeline allows for rapid development of novel gene therapies, addressing previously untreatable conditions. With applications spanning neurology, rare diseases, and oncology, we are building the foundation for the next generation of genetic medicines.

Parrots AI, https://www.flyparrots.com/

Parrots is an AI-powered platform revolutionizing Alzheimer’s care through real-time cognitive monitoring, early detection, and personalized caregiver support. Today, over 55 million people globally live with Alzheimer’s and related dementias, yet current care models rely on infrequent clinical assessments, generic therapies, and overwhelmed caregivers—resulting in delayed interventions, unnecessary hospitalizations, and rising costs.

Parrots transforms this model by using multimodal AI to analyze speech patterns, cognitive engagement, behavior, and wearable data to detect subtle signs of cognitive decline. Our platform delivers daily, personalized cognitive exercises and provides real-time alerts and insights to caregivers and clinicians through intuitive dashboards. This enables early, proactive care decisions and reduces the burden on families and the healthcare system.

Rayo, https://therayo.com

Rayo is an empathetic AI platform transforming digital accessibility by seamlessly bridging user empowerment and business compliance, unlocking a $13T global disability market. Today, 98% of websites remain inaccessible, excluding 400M+ people from jobs, education, and essential services. Current solutions—clunky plugins, slow audits, or niche tools—fail to address both user needs and enterprise compliance.

Rayo changes this with context-aware AI that dynamically adapts digital experiences in real-time. For users, Rayo personalizes interfaces: simplifying layouts, enabling voice/gesture controls, and guiding complex tasks—empowering those with visual, physical, or cognitive disabilities to navigate independently. For businesses, our AI auto-fixes compliance gaps (e g , alt-text, keyboard navigation), generates audit reports, and mitigates legal risks while tapping into an underserved market.

Tangify Corporation, https://tangify.co/

Corporate legal departments already run lean. Now they’re under pressure to cut headcount and still do more with less. Patent programs are especially painful to manage. They require specialized expertise to spot what’s actually patentable, and depend on coordination with senior leaders to make IP decisions. The process of identifying inventions is slow and manual: engineers have to fill out forms, sit through trainings, and attend regular discussions with IP specialists.

Tangify is an agentic AI platform that helps corporate legal teams scale patent discovery – without adding headcount. The platform plugs into existing inventor workflows and reads documents they’re already producing, like engineering specs, meeting notes, jira tickets, marketing whitepapers, etc. It then automatically finds and surfaces overlooked inventions; adds clear, relevant analysis for every invention; supports rapid decision-making; instantly generates supporting patent documentation; and turns scattered technical insights into actionable IP assets at scale.

The Ostrea Cultura Co., https://ostreacultura.com/

Misinformation is a threat to online platforms. It harms users, turns off partners, and exposes platforms to significant regulatory risks. However, there is no way to automatically detect misinformation in real-world contexts. That’s why we, a misinformation researcher and one of the architects of Birdwatch, put our heads together to come up with a solution. We solve the problem by combining human expertise, traditional machine learning, and generative AI into a set of core services for platforms to address misinformation, around misinformation policy, detection, and interventions on platforms ranging from social media to web hosting and parental control. We tap into experts and open-source repositories of misinformation to create a database of false claims. We then use human intelligence and generative AI to create a model that checks any text against this database.

Xtory, www.xtory.ai

Clinical decision-making in the emergency department (ED) is complex, time-sensitive, and prone to errors, leading to poor outcomes, and unnecessary costs ($3.4 B / year in waste). More than 50% of ED visits result in $ loss to hospitals across the U.S. Improving clinical decision-making in the ED leads to increased operational efficiency, optimized workflows, better patient care, and lower healthcare costs.

Xtory is building an AI-powered clinical decision support platform that combines large medical language models with predictive neural networks to help ED clinicians make accurate and timely decisions – our technology enhances clinical judgment while ensuring protocol compliance, improving patient outcomes, and reducing healthcare costs.

yc0n1c, (We are in stealth mode, but can demo the website at anytime.)

Imagine an AI driven, permissionless world where startups don’t chase or pitch for capital—they earn it via validated traction. Where that traction—not talk—unlocks resources. That’s yc0n1c, the global operating system for venture capital and scalable startups—a decentralized infrastructure where every startup is powered by proof, not speculation. Our core is powered by AI-based decision making (yc0n1c), innovative smart contract technology, unified tokenomics and DAO validators. yc0n1c is a living, breathing, on-chain ecosystem where founders, investors, builders, and validators co-create value through programmable smart contract incentives, transparent governance, and an unstoppable feedback loop of traction and trust.

New Videos: Review the FEI25 Collective Intelligence Startup Competition Finalists

Why Collective Intelligence?

Collective intelligence arises from the fusion of human and machine intelligence for results neither could achieve alone. FEI 2025 showcases seed-stage startups that leverage uniquely human tacit knowledge within their AI solutions. By understanding how these new AI offerings are shaped by human experience and intuition, organizations can unlock the power of collective intelligence.

Startups are judged on:

  • Prominent Feature of Human Intelligence as an input
  • Impact and relevance to cross-industry corporates
  • Level of dependence on external ecosystem
  • Disruptiveness/Degree of Difficulty
  • Degree of technical feasibility
  • Customer Desire-ability
  • Business viability

The judges for the 2025 FEI Seed Stage Startup Competition include Keith Crossland, CEO & Co-Founder at Carbon Negative Solutions; Carley Hart, Director of Corporate Partnerships, Runway Startups at Cornell Tech; Andre Magni, Data & AI Leader at Microsoft; Arvind Balasundaram, Executive Director, Commercial Insights & Analytics at Regeneron Pharmaceuticals; Leslie Shannon, Head of Trend and Innovation Scouting at Nokia; Rachel Levy, AI Innovation Engineering Lead at Google; and June Dershewitz, Co-Founder at InvestInData.

FEI 2025 will be held May 19-21, 2025, Omni Boston Hotel at the Seaport Boston. Click here for more registration information.