The Acceleration of Generative AI: How Businesses Are Scaling for Competitive Advantage

In just one year, the business approach to generative artificial intelligence (Gen AI) has undergone a seismic shift. Once viewed as a promising but experimental technology, Gen AI is now a strategic priority for enterprises looking to enhance performance, innovate and stay competitive. Technology leaders in every business and industry will play a central role in this AI-powered digital revolution.

The Hackett Group’s 2025 Enterprise Gen AI Outlook report underscores this transformation with data from the 2025 Key Issues Study: 89% of executives across business functions report that their organizations are actively advancing Gen AI initiatives. This represents a dramatic leap forward from the previous year, when only 16% of executives identified business transformation through Gen AI as a high priority.

This pivot reflects an urgent need to move beyond experimentation and fully integrate Gen AI into enterprise strategy. However, the challenge extends beyond the usual nuts and bolts of new technology adoption – the game-changing nature of Gen AI demands that organizations rethink their operating models, data governance and workforce capabilities if they are to extract meaningful value from AI-driven innovations.

Scaling Gen AI for enterprise success

Embracing Gen AI is not just about enhancing technology service delivery – it’s also about enabling enterprise-wide success. Businesses are fast-tracking Gen AI projects, ensuring dedicated funding and support structures that align with top business objectives. Many organizations are now adopting formalized Gen AI implementation models, ranging from highly centralized to more decentralized, business-embedded structures (Fig. 1).

While these initiatives hold tremendous promise, organizations must also navigate other key challenges, including:

• Data quality and availability: Inconsistent or poor-quality data can hinder AI effectiveness.
• Process and technology complexity: Ensuring smooth integration across business functions is crucial.
• Managing expectations: Organizations must set realistic goals for Gen AI implementation and adoption.

As Gen AI takes center stage in 2025, technology leaders must act with urgency. They hold the responsibility of ensuring that AI adoption aligns with enterprise needs, fuels business priorities and delivers measurable impact.

Gen AI as a catalyst for achieving business objectives

The Hackett Group 2025 Key Issues Study identified the top three enterprise business objectives for 2025:

1. Enhancing customer satisfaction and experiences
2. Increasing market penetration
3. Advancing product and service innovation

This marks a notable shift from enterprise priorities in previous years, when margin improvement and cost containment took precedence. Businesses are focusing on growth and differentiation in 2025, despite economic uncertainty and potential risks. Over half of organizations plan to leverage Gen AI to drive their top objective – enhancing customer satisfaction and experiences (Fig. 2).

While companies see clear opportunities for Gen AI in achieving these goals, they must also contend with evolving risks such as cybersecurity threats, economic fluctuations and regulatory complexities. Adopting a well-structured AI governance framework will be critical in mitigating these risks while ensuring compliance and ethical AI usage.

Cross-functional adoption of Gen AI

While all business functions are still in the early stages of deploying Gen AI, adoption rates are expected to surge over the next year. Business leaders anticipate using AI-driven insights and automation to support their function-specific goals.

These function-specific goals include:

• Procurement: Optimizing category management, supplier relationships and strategic sourcing
• Finance: Improving cash flow, profitability and digital transformation efforts
• Human resources: Enhancing talent management, workforce planning and employee experience
• Payroll and global business services (GBS): Streamlining payroll delivery models and service penetration

The complexity of integrating Gen AI across these diverse functions necessitates strong collaboration between technology leaders and business units. CIOs and technology teams must understand each function’s priorities, provide AI expertise and facilitate seamless AI integration and adoption to maximize enterprise-wide benefits.

Establishing the right Gen AI operating model

To scale Gen AI successfully, companies are adopting various operating models, ranging from highly centralized governance structures to decentralized, business-embedded approaches. The right model for each organization depends on its AI maturity, data infrastructure and existing technology capabilities.

Organizations early in their Gen AI journey often favor centralized models to maintain tight governance and control. In contrast, enterprises with well-established AI foundations are more likely to embrace decentralized models that enable greater flexibility and innovation at the business-unit level.

Regardless of the chosen model, foundational elements for scaling Gen AI include:

• Strong AI strategy and leadership
• Robust data management and architecture
• Ethical AI practices and compliance measures
• Talent development and workforce readiness
• Advanced AI technology enablement

Technology leaders play a crucial role in enabling these elements and fostering a culture of AI-driven innovation across the enterprise.

Measuring the impact of Gen AI

Executives already report seeing measurable value from Gen AI in key areas such as quality, productivity, customer experience and cost efficiency. While most companies currently experience incremental improvements (up to 25%), early adopters who strategically integrate Gen AI are achieving breakthrough results, with quality and productivity gains exceeding 40% in some cases (Fig. 3).

Achieving breakthrough results like these isn’t a given. To unlock Gen AI’s full potential, organizations must overcome a number of critical obstacles.

Key concerns for technology leaders include:

• Process and technology complexity
• Data quality and governance challenges
• Unrealistic benefit expectations

Each of these will require expert knowledge, leadership and guidance from technology leaders to address and overcome. The focus has shifted from Gen AI experimentation to full-scale implementation, making it imperative for technology leaders to take the lead in helping their organizations refine their AI strategies and optimize technology frameworks to achieve meaningful enterprise-wide impact.

Preparing for the future of Gen AI

To accelerate AI-driven transformation and maintain a competitive edge, businesses must focus on the following priorities:

1. Talent acquisition and upskilling: As AI adoption scales, the demand for AI expertise is growing. Organizations must prioritize hiring and upskilling talent in AI-related roles, such as data scientists, machine learning engineers and AI strategists.
2. Enabling AI innovation across business units: Technology leaders should empower business units to explore AI applications while providing the necessary knowledge, guidance, infrastructure, tools and governance to ensure effective and responsible AI use.
3. Addressing AI complexity: Streamlining AI implementation, reducing technical debt and integrating AI with existing systems are all key to maximizing efficiency and minimizing disruptions.
4. Leading by example: Technology teams should actively use AI in their own workflows, demonstrating AI’s potential and fostering a culture of innovation across the enterprise.
5. Assessing AI readiness: A structured approach to AI adoption ensures organizations can scale AI solutions effectively, addressing any roadblocks before full deployment.

Leaders across every organization and function are keen to embrace Gen AI and the fundamental transformation it promises, but to do that they must embrace another, more fundamental key priority, one in which technology leaders must play a critical role: leaders across industries and organizations must rethink and reimagine their work and their workforce to determine specifically where Gen AI can assist and augment human work, and where it can work autonomously. Both the practical technical knowledge and the deeper functional insights of technology leaders will be instrumental to achieving this priority.

The time to act is now

As we enter 2025, businesses that integrate Gen AI into their operations will gain a significant advantage over those that hesitate. Organizations that fail to embrace AI risk falling behind in an increasingly AI-driven world. While AI risks remain a concern, they can be managed through proactive governance, ethical AI frameworks and strategic investments in AI talent and infrastructure.

Early adopters are already redefining work, improving business outcomes and reshaping their competitive landscapes. By adopting a structured approach to AI strategy, use case development, and implementation, businesses can seize opportunities, enhance operational efficiencies and drive long-term growth. Technology leaders will play a primary role in this new information revolution every step of the way.

It’s time to act. Contact us for more information or to schedule a demonstration.