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How to create healthy technology ecosystems

Becoming an AI-fueled organization

In this excerpt from Deloitte’s State of AI in the Enterprise, 4th Edition report, we reveal how a robust and well orchestrated ecosystem strategy can set the foundation for flexibility, stability of resources, and informed perspectives necessary to navigate and compete in an everchanging market.

What is an ecosystem strategy and why does it matter?

No company has all the needed talent, algorithms, data sets, or breadth of perspective in-house to innovate perpetually with AI. That’s largely why most of today’s AI-fueled organizations establish robust technology ecosystems: Through a diverse set of means, they build, partner, license, and access the elements needed to execute their strategy over the long term.

When an ecosystem strategy is robust and well orchestrated, it offers an organization the flexibility, stability of resources, and informed perspectives needed to navigate and compete in an everchanging market. Data from Deloitte's State of AI in the Enterprise, 4th Edition survey reinforced this point: Eighty-three percent of high-achieving organizations (Transformers and Pathseekers) use at least two or more types of ecosystem partners—a significantly higher percentage than low-achieving organizations (Starters and Underachievers). Organizations with more diverse ecosystem relationships also reported stronger preparedness to address AI risk and more confidence in delivering AI ethically.

Most business leaders today understand the importance of building strong ecosystems. However, a common misconception can weaken business leaders’ approach and diminish long-term value: Many mistakenly believe that simple and streamlined ecosystem strategies are more efficient and thus stronger.


How to create healthy technology ecosystems

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Time to diversify: Simple and streamlined tech ecosystems introduce risk

While it may seem counterintuitive, simple and streamlined ecosystems frequently introduce more risk than those that are diverse and complex. Understandably, many leaders attempt to minimize the time and expense of managing multiple relationships, and so they choose to work with the fewest partners needed to meet their goals.

As AI and ML tools become more deeply embedded into an organization’s core operations, it’s important to expand this view. Concentrating resources on too few vendors or partners can lead to overdependence,1 so much so that an organization could become virtually unable to move to a new vendor in the future. In other words, when too many critical business processes rely on a single vendor’s platform and models, it can become extremely difficult to disentangle from them without significant disruption. This can ultimately stymie innovation and growth.


“It needs to be part of the conversation at the beginning and through the whole life cycle about trying to optimize interoperability and avoiding what I would call ‘vendor lock’ as much as possible."

Eileen Vidrine, Chief Data Officer at the US Department of the Air Force

A healthier ecosystem approach

A healthier ecosystem approach typically identifies a base platform and looks for a variety of opportunities to integrate different vendors, including those that may be emerging or niche.

When this approach is executed well, it not only protects from overdependence, but can also result in a higher level of differentiation, flexibility, and access to expanded perspectives on the market.

Survey data reinforced this, showing that organizations with more diverse ecosystems were much more likely to have transformative visions for AI and use AI as a strategic differentiator. Of course, thoughtful orchestration of these relationships is required to achieve such outcomes. Deciding how to leverage each one is just as important as who and how many.

Which elements your organization decides to build in-house versus buy or license externally is an important strategic exercise that can’t be overvalued. Each decision should come down to one central question: How does each relationship support and protect your organization’s ongoing competitive differentiation in the market?

"Emergent technology domains, like artificial intelligence, are evolving too fast and in too many directions for most companies to keep pace. This demands a
more fluid and hybrid approach—buy, lease, invent, experiment, and partner with a variety of external organizations that compliment and extend your company’s competitive edge.” 

Keith Strier, Vice President of worldwide AI initiatives at Nvidia


End notes: 

1 Justice Opara-Martins, Reza Sahandi, and Feng Tian, “Critical analysis of vendor lock-in and its impact on cloud computing migration: a business perspective,” Journal of Cloud Computing 5, no. 4 (2016).


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