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Four AI Futures for Enterprise Tech

Four AI Futures for Enterprise Tech
By
The Information Partnerships

Expectations about the impact of artificial intelligence on business are running high, but how will AI deployment unfold? The Information’s readers were presented with a survey detailing four different scenarios about how AI will play out in their companies, as defined by the EY organization, in the near and midrange future.

Through careful analysis of emerging signals and trends, EY professionals have identified “four futures of AI” distinct scenarios for how AI could reshape the business landscape by 2030. These range from steady evolution to transformative change, from a cautious recalibration to a concentration of market power. While not predictions, these scenarios serve as tools for strategic thinking, helping leaders prepare for various possible outcomes.

These futures are:

  • Growth: AI leads to evolved business models with agentic workflows.
  • Transform: Artificial general intelligence reshapes enterprises without humans.
  • Constraint: AI regulation paces AI progress and tech advancements.
  • Collapse: AI concentrates power in one dominant entity.

Here is how 261 readers of The Information see as the most likely ways in which AI deployment will proceed, and what its major impacts and drivers will be along the way.

The Growth Future Comes Out On Top

Over the next 12 months, a majority (72%) of The Information’s readers expect to see the Growth scenario, where AI systems help people work faster and better, enabling them to manage and complete entire processes and workflows far more effectively (see chart).

But readers point out that the AI deployment will be gradual. “Unless they are in niche industries, it’s going to be a slow rollout with limited impact on the processes, as people internally adopt AI solutions,” says one reader. “We are preparing with that in mind, starting with low-hanging fruit to ease adoption and comfort levels. At the same time, this approach allows us to keep an eye on trends and players to better understand how to pursue the more advanced use cases.”

Another reader adds that the Growth scenario may in fact become slow growth. “It will take longer than we expect to unlock efficiency or business model value from AI except in very specific use cases, such as accelerating coding,” says the reader.

Dan Diasio, EY global consulting AI leader, points out that companies will not be able to thrive without successfully harnessing AI. “As we navigate the evolving landscape of AI, it’s clear that the future will be shaped by our ability to adapt and innovate. A future where AI enhances workflows and productivity is not just a possibility; it’s a necessity for businesses aiming to thrive in a competitive environment,” he says.

Forty percent of The Information’s readers expect that the next 12 months will see companies doing a deeper dive into AI rather than going for the relatively low-hanging fruit suggested in the Growth future. They believe what will unfold will be the Transform future, where advanced AI systems lead to workforce and business reinvention. Looking three years out, a majority of The Information’s survey respondents (55%) believe AI will have led to business and workforce reinvention.

A minority of The Information’s readers predict that the two of the more challenging scenarios will materialize. Fifteen percent anticipate the Constraint future within the next 12 months, under which malfunctions and mistakes will lead to reassessment of AI systems.

Some of The Information’s readers warn that malfunctions are a very real possibility. “The current pace of activity is accompanied by a lack of investment in quality assurance, testing and security. This will result in some major failures that will lead to a more considered and rigorous approach,” says one reader. Agrees another: “There will be many missteps because so many companies are just looking to be able to say that they are implementing generative AI rather than doing it in a thoughtful manner that will be transformative to their business.”

“Having a strong handle on the frontier AI capabilities, instead of getting caught in the hype, will help companies avoid an erosion of credibility inside and outside their organizations. Furthermore, knowledge of the frontier should drive architecture patterns and use case decisions, so companies’ initiatives get more valuable as the AI gets better,” says Diasio.

Twenty-two percent of The Information’s survey respondents anticipate the Collapse future within the next 12 months, which would upend business dynamics due to market concentration of AI providers. “Similar to how we are dependent on cloud providers to host software deployments, we will be dependent on AI labs as they will be integrated into every faucet of IT,” says one reader.

Preparing for Incremental Change

The adage of “hope for the best, prepare for the worst,” does not seem to apply to how The Information’s readers view their readiness for different AI futures. They are less prepared for the more challenging futures than for the smoother ones:

  • A majority believe they are prepared for the Growth future. 
  • Less than half consider themselves prepared for the Transform future.
  • Less than a third consider themselves prepared for the Constraint or Collapse futures.

One of The Information’s readers points to the importance of being well prepared to succeed at implementing AI: “I can be positive on AI futures for those companies that appreciate the need for change and have the capabilities to build AI in their operations.”

Another of The Information’s readers confirms that some companies may not yet be prepared for AI implementation and stresses the risks that go with it: “My company does not yet have a defined strategy but will need to develop one within the next one to two years or risk losing competitiveness.” Others recognize the need to prepare the organization for AI. “We emphasize cultural transformation that promotes agility, accountability and openness to integrating AI-driven processes into daily activities,” says one reader.

EY consulting leader Diasio underscores the need for and importance of change management to succeed at AI in an enterprise: “Responding to an exponential capability, unfolding over months and not decades, requires a deep focus on culture. Organizations need to build change muscles within every function and every business across the enterprise. It’s not just about upskilling; it’s the constant questioning of why we do what we do, every single day.”

Sixty-three percent of the survey respondents are prepared for the Growth future, which anticipates incremental increases in productivity and efficiency. The benefits of AI under the Growth future focus on speed and effectiveness, which can be seen as relatively easy wins. Fewer of The Information’s survey respondents (38%) are prepared for the Transform future, which leads to faster, deeper changes and reinvention of the business models. Such deeper reinvention arguably requires more preparation by the enterprise.

Even fewer of The Information’s readers believe their companies are prepared for the Constraint and Collapse scenarios at 28% and 26%, respectively. These two futures might be propelled by as-yet-unknown triggers, such as AI lab concentration or emerging AI malfunctions. The preparation for such futures requires not just structural changes but also built-in agility and the right resources in place to be able to pivot when necessary.

What Will Move the Needle?

These AI futures will not be playing out in a vacuum, and survey respondents expect to be modifying their AI rollouts over the next three years. The top factors impacting their businesses, they believe, will be the increased focus on discrete applications (64%) and the need for additional human oversight (63%).

They see implementing AI for discrete applications as a realistic approach to AI. “While most companies will struggle with AI, those that focus on more narrow and tightly defined use cases will make much more progress. There simply isn’t enough talent to move quickly and more ambitiously at the same time,” says one reader. Another one puts it more bluntly: “AI is useful in small, controlled environments fed with discrete and specific information and walled off from the general internet. Broad adoption of AI to streamline all business is a pipe dream that will backfire spectacularly.”

At the same time, however, others believe (58%) that one of the impacts of AI will be increased market concentration around companies with access to dominant AI capabilities. This concentration will happen around “newer firms with AI-first capabilities that will crush many of the existing enterprise companies,” says one of The Information’s readers. This outcome would put an onus on existing enterprises to keep pace with the AI natives.

One of The Information’s readers views human oversight as a must: “As a business owner, I have saved a large amount of capital by using AI. However, if we use it without verifying the information produced by AI, we could be blacklisted in the industry we serve.”

Another reader suggests that to succeed, AI itself should be treated like a human—albeit a junior-level one: “Human teams should treat AI like an intern or junior employee and start training AI agents to do tasks. The training data should be kept separate so it can be reused as more powerful AI infrastructure develops.”

What Does — And Doesn’t — Drive AI Rollout

According to the respondents, the top driver of an AI rollout boils down to one fundamental decision: What are the right use cases for AI (61%)? The majority believe many of the other drivers, such as achieving return on investment, having the right talent in place or integration with current systems and processes, cannot be achieved without having selected the right use case in the first place.

For some companies, selecting the right use cases calls for patience: “[Our AI strategy] is high enthusiasm but slow implementation as we work through use cases and then apply learnings to make plans to expand utilization.”

Another of The Information’s readers believes a successful use case should spearhead more AI success: “Lean into the successful AI use cases. See where they take the business.”

Integration of AI solutions within existing systems and advances in AI technology is also a major driver for AI implementation (58%). The ability to integrate AI is often predicated on the advances in AI technology. The recent advances, according to one reader, mean that “while so far, simply waiting for the next model generation has generally been the best way to develop with AI, today pretty much every previous use case that required scaffolding can just be solved by the models themselves.” However, another reader stresses that AI technology has not yet reached its full potential: “AI technology still needs a few steps with increasing its capabilities and also the tooling around building agents and workflows, and the integration with existing platforms.”

Conclusion: Will You Shape the Future of AI, Or Will It Shape You?

Most of the business leaders surveyed expect the deployment of AI solutions to follow the Growth scenario, but others predict that different AI futures, as defined by the EY organization, may also unfold.

These futures range from a total business reinvention to constraints due to AI malfunctions and even collapse in AI deployment caused by the market dominance of a select group of AI labs. Companies that are not prepared for different AI futures risk derailment by the forces of AI and falling behind the competition. Every company needs to consider the following AI-related questions:

  • How will different AI futures manifest and when? 
  • How can the company best track the trends and stay ahead of the curve in AI developments?
  • How can it prepare for different AI futures—from Growth to Collapse—while deploying AI solutions? 

Take a deeper dive into the EY four futures of AI.

METHODOLOGY

This report is based on a survey of 261 readers of The Information, fielded in March and April 2025. The respondents represented multiple industries, company sizes, functional areas and ranks. Specifically:

  • Industry: The biggest number of survey respondents came from technology, media and telecommunications (35%); professional services (18%); and financial services and capital markets (11%). 
  • Company size: Forty-eight percent of the survey respondents came from companies with revenues under $10 million; 18% had revenues between $10 million and $100 million; 7% had revenues between $100 million and $500 million; 2% had revenues between $500 million and $1 billion; 9% had revenues between $1 billion and $5 billion; and 15% had revenues of more than $5 billion. 
  • Functional area: The most represented functional areas were general management (33%); information technology (13%); and marketing and communications (12%).
  • Title: The most represented were directors (18%); followed by CEOs (17%); employees (13%); CEO-owners (13%); and chief information officers or technology officers (11%). 

The views reflected in this article are the views of the author and do not necessarily reflect the views of Ernst & Young LLP or other members of the global EY organization.