21 October 2021


How does your organization measure up?

Take a three minute quiz to find out how your organization compares to our AI-fueled market segments and which leading practices could help advance your transformation journey most.


morbi tristique

Who is leading the AI market today?

AI-fueled organizations leverage data as an asset and scale human-centered AI across all core business processes. They use rapid, data-driven decision-making to enhance workforce and customer experiences. Our research uncovered four types of companies that are progressing toward this ideal. Click or tap on the boxes below to learn about these four profiles.

Outcomes achieved (high degree)






High outcome Low deployed





High outcome High deployed









Low outcome Low deployed







Low outcome High deployed


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AI application types fully deployed


753 executives | 26% total survey population

Pathseekers have adopted capabilities and behaviors that are leading to success, but on fewer initiatives. In other words, they are making the right moves but have not scaled to the same degree as Transformers. They average 1.9 out of 10 possible full-scale deployments of different types of AI applications, and 6.2 out of 17 possible outcomes achieved to a high degree.



794 executives | 28% total survey population

Transforming but not fully transformed, this group has identified and largely adopted leading practices associated with the strongest AI outcomes. They average 5.9 out of 10 possible full-scale deployments of different types of AI applications, and 6.8 out of 17 possible outcomes achieved to a high degree.



832 executives | 29% total survey population

Getting a late start in building AI capabilities seems to characterize this group; they are the least likely to demonstrate leading practice behaviors. They average 1.6 out of 10 possible full-scale deployments of different types of AI applications, and 1 out of 17 possible outcomes achieved to a high degree.



496 executives | 17% total survey population

A significant amount of development and deployment activity characterizes this group; however, they haven’t adopted enough leading practices to help them effectively achieve more meaningful outcomes. They average 5.6 out of 10 possible full-scale deployments of different types of AI applications, and 1.4 out of 17 possible outcomes achieved to a high degree.


Leading practices for becoming AI-fueled

AI success is typically built upon the foundation of a clear, well-communicated strategy, business-led work transformation, documented development standards, an adaptive workforce, and a robust set of ecosystem partners. We found that these leading practices (strategy, operations, culture and change management, and ecosystems) make up the four cornerstones of AI-fueled organizations.


Transformers were three times more likely to have an enterprise-wide AI strategy in place. What can you learn from them?

1. Put strategy first

Link your AI strategy to the company’s strategic north star and navigate AI investments by it.

2. Automate and innovate

Don’t over-index on efficiency gains. With AI, you can reimagine the way you do business too.

3. Share your vision

Bold visions motivate big results. Public awareness attracts talent and investment.

4. Keep iterating

Develop dynamic ways to assess and adjust your strategy so that it evolves with the market.

How are strategists making more clear, timely, and creative choices about where to play and how to win?

Find out


Implementing new tech like AI often requires new ways of operating. Only about a third of companies surveyed, however, said that they’ve adopted leading operational practices. How can you rethink your operations from both a business and IT perspective?

1. Ensure the business leads

It’s tempting to let data scientists lead the application of a data-driven technology, but business requirements come first.

2. Reimagine workflows and roles

Organizations that have undergone significant changes to workflows or added new roles are almost 1.5 times more likely to achieve outcomes to a high degree.

3. Put MLOps processes in place

DevOps isn’t enough. ML development and maintenance require unique approaches. Organizations that strongly adhere to these processes are three times more likely to achieve their goals and deliver AI in a trustworthy way.

How should organizations rethink their operations to ensure quality AI solution development, enterprise adoption, and the most successful outcomes?

Find out

Culture and change management

Strong AI outcomes require trust, data-fluency, and agility. Why is leveraging change management to create the right culture so important?

1. Trust overcomes fear

Bold AI visions elicit healthy and unhealthy fear. Trust keeps your workforce moving forward through it.

2. Data fluency drives creative insights

Data-literacy skills build confidence and trust in AI, which helps set organizations up for positive outcomes.

3. Agility helps you fail fast

AI-fueled organizations turn insights into rapid experimentation and can pivot quickly after failure.

What impact does rapid technology transformation have on the workforce’s ability to adapt, perpetually learn new skills, and make decisions amid growing ambiguity?

Find out


When an ecosystem strategy is diverse and well-orchestrated, it offers flexibility, stability, and perspective. 83% of responding high-achieving organizations use two or more types of ecosystem partners. How do we build dynamic ecosystems?

1. Choose partners with diverse perspectives

Organizations with diverse ecosystems are significantly more likely to have a transformative vision for AI, enterprise-wide AI strategies, and use AI as a strategic differentiator.

2. Keep things complicated

Too few external partnerships can make it difficult to part ways with vendors if needed in the future.

How can an ecosystem strategy set the foundation for flexibility, stability of resources, and informed perspectives necessary to navigate and compete in an everchanging market?

Find out

Our AI-fueled future: The pathway is clear

We’re rapidly approaching the day when AI is expected to independently and reliably illuminate creative and strategic opportunity, releasing us from the confines of our limited perspectives. As we advance further into that AI-fueled future, organizations that dedicate their imagination and energy to laying the foundations now could be rewarded manyfold.

About the survey

We surveyed 2,875 executives from 11 top economies who have purview into AI strategies and investments within their organizations. We asked them about a wide variety of behaviors—from their overarching AI strategy and leadership, to their technology and data approaches, and how they’re helping their workforce operationalize AI. Then, to understand which behaviors lead to the greatest outcomes, we analyzed the survey responses based on how many types of AI applications a company has deployed full scale and the number of outcomes achieved to a high degree.

Get connected

Talk with us about your path to becoming an AI-fueled organization.

Deloitte AI Institute

The Deloitte AI Institute helps organizations connect all the different dimensions of the robust, highly dynamic and rapidly evolving AI ecosystem. The AI Institute leads conversations on applied AI innovation across industries, with cutting-edge insights, to promote human-machine collaboration in the “Age of With.”

Contact us

Nitin Mittal

Nitin Mittal

Principal | Deloitte AI

Deloitte Consulting LLP
Irfan Saif

Irfan Saif

Principal | Chief Strategy Officer

Deloitte & Touche LLP
Beena Ammanath

Beena Ammanath

Executive Director of Deloitte AI Institute

Deloitte Consulting LLP