- Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
- To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
- This is part 10: Open innovation & ecosystems.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
This is part 10: Open innovation & ecosystems.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
This is part 10: Open innovation & ecosystems.
Innovation doesn’t happen in a vacuum
It’s a team sport—and no organization can change the game on its own. Ecosystem partnerships, where solution and service providers combine their skills and capabilities to deliver strategic outcomes, are essential to deliver innovations that are truly transformative. Past IBM IBV research found that organizations investing in ecosystems gain a revenue growth premium of 40%. And these investments could become even more lucrative in the age of generative AI.
Generative AI can ignite ecosystem innovation by tapping into the collective brainpower of all the organizations quickly and easily. By synthesizing their shared expertise, it can brainstorm potential solutions to big problems, predict which products will be the most successful, and optimize project plans to deliver desired outcomes. But this synthesis depends on deep stores of data, massive computing power, and in-demand skills.
That’s why gaining a competitive edge with generative AI will require sharing the load with ecosystem partners—and breaking down internal and external barriers. Openness is central to this process, as the data it requires sits in multiple organizations, applications, silos, clouds, and lakes.
Of course, openness must always be accompanied by good governance. To ensure innovations are both ethical and secure, CEOs should ensure that ecosystem partners bring the right talent, technology, and customer relationships to the table, and gauge whether partners share their principles and values. As the next generation of generative AI models quickly comes of age, ecosystem-fueled innovation must be built on a rock-solid foundation of transparency and trust.
The IBM Institute for Business Value has identified three things every leader needs to know:
1. Generative AI reinvents innovation—and the value of ecosystem contributions.
2. Innovation will become the new ordinary.
3. Partnerships that worked in the past might not be right for the future.
And three things every leader needs to do right now:
1. Innovate the way you innovate.
2. Prepare your organization to do higher-value work with cross-ecosystem skills.
3. Reevaluate your relationship status.
An updated version of this chapter with 2024 data is now available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
Additional content
Meet the authors
Cindy Anderson, Global Executive for Engagement and Eminence, IBM Institute for Business ValueChristian Bieck, Europe Leader & Global Research Leader, Insurance, IBM Institute for Business Value
Anthony Marshall, Senior Research Director, Thought Leadership, IBM Institute for Business Value
Jacob Dencik, Ph.D, Research Director, IBM Institute for Business Value
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Originally published 20 November 2023
1. Innovation
+ Generative AI
What you need to know
Generative AI reinvents innovation—and the value of ecosystem contributions
Generative AI isn’t just another tool in the innovation toolbox. It’s the entire workshop.
Every day, people are discovering new ways to use generative AI to automate tasks, make business decisions, and plan for future disruption. And no leader wants to be left behind.
Roughly half of CEOs feel pressure from business partners to accelerate adoption of generative AI—and two-thirds of executives say their organization needs to quickly adopt generative AI for innovation. However, only 39% of organizations are currently implementing or operating generative AI for innovation and research.
The organizations blazing the trail could see big dividends. Innovation outperformers see annual revenue growth that is 74% higher than their peers. Generative AI promises to upgrade ecosystem innovation by transforming the entire workflow. A large majority of executives say generative AI will greatly improve ideation (80%), discovery (82%), collaboration with partners for innovation (77%), and innovation execution (74%).
To make the most of this opportunity, CEOs may need to rethink how the entire business operates. By taking a high-level view of strategy—and being willing to go back to the drawing board—leaders can find new ways to deliver and capture value within ecosystem partnerships.
What you need to do
Innovate the way you innovate
Use generative AI to spark creativity and enhance collaboration throughout the innovation cycle. Synthesize expertise across the ecosystem to solve complex problems, develop competitive products, and disrupt traditional business models.
- Turn generative AI into an innovation game-changer. Unlocking the value of generative AI for innovation will require changes across the innovation operating model. Pursue it as a transformative opportunity for greater innovation efficiency and effectiveness.
- Augment and automate to enhance innovation. Adopt generative AI across the innovation workflow for greater speed, scale, and impact. Use automation to free up talent to take greater ownership of innovation workflows across the enterprise.
- Introduce experimentation at scale. Hypothesize, trial, and adjust how generative AI is applied to innovation in a controlled manner. Measure generative AI innovation outcomes against “manual” outcomes to prove value.
2. People
+ Generative AI
What you need to know
Innovation will become the new ordinary
Generative AI frees employees from the mundane and helps them realize their untapped potential. However, capability constraints often block AI-powered innovation, both within the organization and across the ecosystem.
More than two-thirds (69%) of organizations expect to use generative AI for open innovation by 2025—up from 29% in 2022. But only 38% of executives say their organization has the in-house expertise to adopt generative AI for innovation. Fewer than half of executives say their organization has identified specific innovation use cases for generative AI (45%) and is ready to adopt generative AI for innovation responsibly (48%).
To work more effectively with external partners, CEOs must first remove roadblocks. While adopting generative AI for open innovation requires access to cutting-edge tools, executives say their top barriers relate to data and people, not technology. Concerns about data privacy, confidentiality, and security top the list, followed by inadequate generative AI skills and expertise.
Yet, executives are hopeful that generative AI will help strengthen their teams’ innovation chops. A full 92% of executives looking to apply generative AI to innovation say they plan to augment employees with generative AI rather than replace them.
What you need to do
Prepare your organization to do higher-value work with cross-ecosystem skills
Unleash the potential of generative AI-powered ecosystem innovation by addressing internal roadblocks. Build and develop data, skills, and culture as critical ingredients to drive long-term ecosystem success.
- Fuel innovation with premium data from inside and outside the enterprise. Develop clear data governance mechanisms to ensure transparency and trust. Create an enterprise data fabric that makes data available where it’s needed across the enterprise. Break down data silos to make it easier to share data with partners.
- Tap into employees’ inner innovator and extend capabilities outward. Define, build, and manage organizational capabilities and skills for innovation and generative AI. Make change management an integral part of your innovation and generative AI journey. Work with ecosystem partners to enhance capabilities.
- Let culture eat tech for breakfast. Adapt incentive mechanisms and KPIs to encourage collaboration and innovation with generative AI. Allocate decision rights to drive innovation across the enterprise.
3. Ecosystem
+ Generative AI
What you need to know
Partnerships that worked in the past might not be right for the future
Generative AI has put everything on the negotiating table—and opened the door to unprecedented business propositions.
In this environment, executives are looking for partners in new places, and they’re hoping generative AI can help. In fact, executives expect expanding the innovation ecosystem to be the top benefit that comes from using generative AI for innovation.
But successful ecosystem partnerships are about quality—not just quantity. As CEOs apply generative AI to ecosystem innovation, they need to be selective about who they bring to the table. By first assessing their own strengths—and identifying critical gaps—leaders can determine where the organization needs the most support, whether that translates to complementary expertise, specialized data capabilities, or better market access.
Leaders should use the generative AI moment as an opportunity to reassess their existing partnerships and align their ecosystem around common standards and shared values. Understanding the strategic value of the organization’s proprietary data, as well as where it resides—in which applications, with known ownership— should be part of this process. Defining the competitive advantage it can deliver—and how it will capture value from the partnership in question—will help leaders decide when and where to share intel with ecosystem partners to fuel innovation.
What you need to do
Reevaluate your relationship status
It’s time to tap your ecosystem’s collective intelligence. Assess whether you have the right partners to spur your innovation forward—and be prepared to swipe left.
- Refresh innovation strategy through new ecosystem partnerships. Engage partners for more data, more insights, more discoveries, and better outcomes. Focus on partnerships that provide more pathways for rapid adaptation and access to a broader range of capabilities and technologies. Be clear about what is unique to your organization, what needs to be proprietary, and how your partners will complement what you already have.
- Build a new relationship checklist. Assess partners for a common understanding of necessary AI guardrails and principles. Establish clear governance and standards to foster trusted and secure collaboration and innovation. Be clear on deal-breakers.
- Expand your ecosystem EQ. Collaborate and co-create using hybrid cloud and open AI platforms for shared data. Embrace open standards and ensure complementarity and compatibility.
The statistics informing the insights on this page are sourced from two proprietary surveys conducted by the IBM Institute for Business Value and Oxford Economics, as well as several published IBM Institute for Business Value reports. The first survey included 315 executives in the US, UK, Germany, Australia, and Singapore and was conducted during May and June 2023, asking respondents about the application of generative AI for open innovation. The second survey included 300 US-based executives and was conducted in May 2023, asking respondents about the impact of generative AI on the workforce. Findings from CEO decision-making in the age of AI (2023), Extending digital acceleration (2021), and Open the door to open innovation (2021) are also incorporated.
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An updated version of this chapter with 2024 data is now available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
Additional content
Meet the authors
Cindy Anderson, Global Executive for Engagement and Eminence, IBM Institute for Business ValueChristian Bieck, Europe Leader & Global Research Leader, Insurance, IBM Institute for Business Value
Anthony Marshall, Senior Research Director, Thought Leadership, IBM Institute for Business Value
Jacob Dencik, Ph.D, Research Director, IBM Institute for Business Value
Download report translations
Originally published 20 November 2023
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