Discover which of the four futures of AI aligns with your strategic vision 

The explosive growth of artificial intelligence (AI) presents business leaders with both extraordinary opportunities and new strategic challenges. While 99% of CEOs say their companies are investing in AI, the path forward remains unclear. New capabilities emerge almost daily, promising substantial efficiency gains and productivity improvements. Some have heralded the dawn of a new “golden age” for the global economy.

Yet this promise comes amid a volatile, uncertain, complex and ambiguous (VUCA) environment surrounding AI. The dizzying pace of technological advancement has created enormous hype and speculation. Behind the excitement looms considerable risks — not just around AI safety and control but also around threats to workforce stability and human livelihoods. For many organizations, transforming with AI raises the prospect of massive structural change and disruption to existing business and operating models, emphasizing the importance of AI regulation.

Through careful analysis of emerging signals and trends, we have identified four distinct scenarios for how AI could reshape the business landscape by 2030. These AI futures 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.

Are you ready to learn more about each future of AI?

As your organization navigates the AI transformation journey, these scenarios provide a framework for strategic planning and risk assessment. Which AI future aligns with your strategic vision? What capabilities and market positions should you build today to thrive in each potential future of AI? Most importantly, how can you influence which future materializes?

Agentic AI drives progress across industries, unlocking new efficiencies and capabilities.

In this future, AI capabilities advance steadily along current trajectories, driven by incremental improvements rather than major breakthroughs. Efforts to regulate the technology are outweighed by productivity gains from humans leveraging AI. By 2030, domain-specific AI agents have achieved remarkable proficiency in operational functions across finance, HR, legal and other business areas. This evolution enables new organizational models featuring highly automated back offices and AI-augmented front offices, delivering significant productivity gains and cost efficiencies.

Key characteristics of this future of AI 

Strategic considerations for executives:

 
  • How will you identify and prioritize the most valuable AI use cases for your organization?
  • How will you integrate digital workers with human workers?
  • How can you transform operations while maintaining business continuity?
  • What investment approach will support sustained AI adoption?
  • How will you measure AI-driven progress and organizational resilience?
  • What leadership capabilities are needed to guide this evolution?

Traits of successful organizations:

 

  • Clear AI governance frameworks that balance innovation with risk management
  • Strong change management capabilities for workforce transformation
  • Robust data infrastructure and analytics capabilities
  • A commitment to continuous learning and skills development
  • Balanced investment approaches across technology, people and processes

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AGI accelerates innovation, sparking entirely new ways of working and transforming society.

In this future of AI, the widespread adoption of advanced reasoning and agentic AI systems creates unprecedented opportunities for business innovation and value creation. By 2030, enterprise-grade AI platforms have become robust, trustworthy and widely accessible, massively augmenting human capabilities and automating even complex workflows and activities across multiple domains. Democratizing AI enables organizations to completely reimagine how they work, creating lightweight and remarkably efficient organizational structures that enable human creativity and strategic thinking to be unleashed while unlocking latent market demand.

Key characteristics of this future of AI 

Strategic considerations for executives:

 

  • What future-proof AI investments are you making today?
  • How are you evolving your business model for this transformed landscape?
  • Are your systems and culture prepared for AI-augmented workforces?
  • How can you build an AI-first organization while maintaining human-centric values?
  • What role will human talent play in your AI-enabled future?
  • How are you preparing for new forms of competition?

Traits of successful organizations:

 

  • Strong capabilities in AI platform development and integration
  • Innovative approaches to human-AI collaboration
  • Sophisticated data governance and value creation frameworks
  • Agile organizational structures that support rapid innovation
  • Forward-thinking talent development and acquisition strategies

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Faulty AI in sectors lead to public outcry as people demand stricter controls and transparency.

In this future of AI, adoption of the technology faces significant recalibration following a series of high-profile setbacks. By 2030, incidents such as AI trading system malfunctions impacting market stability, persistent errors in AI-powered financial reporting and medical AI misdiagnoses have led to new liability issues. Meanwhile, AI content generation has proved less commercially viable than anticipated. These challenges prompt a measured reassessment of AI regulation and AI implementation across markets.

Key characteristics of this future of AI 

Strategic considerations for executives:

 

  • How are you future-proofing AI governance frameworks?
  • What methods are you using to evaluate AI reliability and risk?
  • How do you manage and learn from AI system errors?
  • What is your strategy for balancing innovation with risk management?
  • How can you build stakeholder trust through clear AI policies?
  • What mechanisms will you use to enforce AI governance?

Traits of successful organizations:

 

  • Robust risk assessment and validation processes
  • Clear frameworks for human oversight of AI systems
  • Strong stakeholder communication and trust-building capabilities
  • Flexible operational models that can adapt to varying requirements of AI regulation
  • Balanced approaches to automation that prioritize reliability over speed
  • A full view of their value chains, internally and externally, and the AI fueling them

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AI enables a monopoly to control key infrastructure globally, hindering competitors.

In this future of AI, a major technological breakthrough leads to extreme market concentration in AI capabilities. By 2030, a single entity achieves significant advantages in AI, creating powerful network effects that reshape market dynamics across all knowledge-based sectors of the economy.

Key characteristics of this future of AI 

Strategic considerations for executives:

 

  • How will dominant AI capabilities disrupt your sector, and what is your pivot strategy?
  • Does your organization have the agility to respond rapidly to market shifts?
  • What safeguards can reduce reliance on a single AI provider?
  • How can you protect core intellectual property and talent?
  • What competitive advantages can you maintain independently?
  • How might your role in the value chain evolve?

Traits of successful organizations:

 

  • Strong capabilities in niche areas that complement dominant AI platforms
  • Robust risk management and business continuity planning
  • A clear understanding of the organization’s core competitive advantages (also known as its AI moat)
  • Flexible partnership strategies that maintain some autonomy
  • A strong focus on unique data assets and proprietary capabilities

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Actions to take 

The current AI landscape is defined by volatility, uncertainty, complexity and ambiguity (VUCA). Understanding what the future of AI has in store for organizations is only the first step. As we ask ourselves, “How will AI shape our future?” we must also prioritize readiness strategies for people and enterprise.

Summary

While the future of AI remains uncertain and unpredictable, we have envisioned four distinct scenarios that could shape our world:

  1. "Growth," representing steady advancements across various industries
  2. "Transform," characterized by the emergence of artificial general intelligence that could fundamentally reshape organizations
  3. "Constraint," where regulation may limit the rapid adoption of AI
  4. "Control," which warns of monopolistic dominance that could disrupt market dynamics

Each of these futures presents unique opportunities and challenges. To thrive in this evolving landscape, organizations will need to continuously strategize, innovate and prepare for what could come next.


Vote for the AI future you are preparing for

We polled industry leaders to see what potential AI future they are preparing for within their own organizations. At initial polling, half of respondents said that they think the growth future - in which AI drives steady progress across industries - will be most likely.

See what other readers think will be the future of AI and add your vote below!

How EY can help

Meet the leaders

Matt Barrington

EY Americas Chief Technology Officer
Technology practitioner and strategist. Maker. Husband. Proud father. Weekend farmer.
Charlotte, USA

Hugh Burgin

EY Americas AI and Data Analytics Leader
Deep knowledge in strategy, AI, machine learning and automation. Has lived and worked around the world.
Denver, USA

Whitt Butler

EY Americas Vice Chair – Consulting
Transformational leader driven by values and purpose. Global strategist and innovator. People-focused team builder. Proud husband and father. Golf enthusiast.
Akron, USA

Dan Diasio

EY Global Consulting AI Leader
Contributing to a positive, responsible future for our people and the next generation. Connector. Curious about the new and the old. Husband and Papa.
New York, USA

John Dubois

EY Americas AI Strategy Leader
Entrepreneur. Consultant. Mentor. Puts clients and colleagues first, knowing the financial results will follow.
Austin, USA

Sameer Gupta

EY North America Financial Services Organization Advanced Analytics Leader
Leader of a strong cross-functional team focused on solving complex business problems with AI-driven approaches. Hobbyist woodworker. Culinary enthusiast. Father.
New York, USA

Traci Gusher

EY Americas AI and Data Leader
Uses advanced analytics and artificial intelligence to bring value to clients’ challenging issues and opportunities. Experienced triathlete. Passionate about animal rescue and cancer research.
Philadelphia, USA

Samta Kapoor

EY Americas Energy AI and Trusted AI Leader
Tech evangelist and strategist. AI and data innovator. Proud wife, mother and salsa lover. Passionate about and dedicated to ethical tech growth and tackling world hunger.
San Francisco, USA

Harvey Lewis

Partner, Technology Consulting, Ernst & Young LLP
AI thinker. Public speaker. Writer. Rocket scientist. Husband and father. Dog walker.
London, GBR

Rakesh Malhotra

Principal, Digital & Emerging Technologies, Ernst & Young LLP
Product leader focused on intelligent distributed platforms. Entrepreneur. Passionate about sports, wine and travel.
Hoboken, USA

Vidhya Sekhar

EY Americas Financial Services Data and Analytics Leader
Data and analytics professional. Problem solver. Team player. Working mother. Realist.
Hoboken, USA

Yang Shim

EY Americas Technology Consulting Leader
Focused on driving technology transformation, innovation and strategy. Husband. Father. Volunteer. Golfer. Hockey fan. Supports diversity and inclusion.
Tysons, USA

Kapish Vanvaria

EY Global and Americas Risk Consulting Leader
Innovative transformation leader in risk consulting. Change agent and lifelong learner. Passionate about developing the next generation of business leaders.
Philadelphia, USA

Vignesh Veerasamy

EY Americas AI Transformation Leader
Strategic thinker. Complex problem solver. Innovation enthusiast. People focused.
San Francisco, USA

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