The Future of Generative AI: From Exploration to Enterprise Acceleration

In just one year the landscape of generative artificial intelligence (Gen AI) has shifted dramatically. What was once an experimental endeavor has now become a strategic imperative for businesses seeking to enhance performance and gain a competitive edge. According to The Hackett Group’s 2025 Enterprise Key Issues Study, 89% of executives report that their organizations are advancing Gen AI initiatives. This stands in stark contrast to the previous year, when only 16% of executives prioritized business transformation through Gen AI.

Companies are expediting Gen AI projects to align with their top business objectives. Most organizations now support their initiatives with formal models – ranging from centralized frameworks to decentralized, business-embedded structures. To unlock Gen AI’s full potential, however, businesses must overcome challenges related to data quality and process and technology complexity, and they must set realistic expectations regarding the benefits.

The rise of Gen AI assistants and agents

One of the great underrecognized challenges facing organizations prioritizing and moving ahead with Gen AI is to reimagine their work and their workforce to determine the role AI assistants and agents will play: where AI can assist human performance, where it can augment human performance, and where it can work autonomously.

Defining Al

Assistants: Intelligent applications that understand natural language and use conversational interfaces to complete tasks on behalf of users.

Agents: Intelligent applications that perform tasks autonomously on behalf of users or other systems without the need for constant human intervention.

Together these tools are poised to revolutionize operations by enhancing efficiency, reducing manual errors and providing real-time insights that enable more agile decision-making.

Gen AI is a transformative force that has only just begun to reshape work and the workforce. Organizations that fail to integrate Gen AI assistants and agents into their workflows will fall behind in an increasingly AI-driven economy.

By deploying these capabilities businesses are redefining how work gets done, leading to higher levels of customer satisfaction, increased market penetration, and improved product and service innovation – the top three enterprise business objectives for 2025. This marks a shift in priorities from the previous year, when margin improvement and protection were the primary focus. Even in the face of economic uncertainty, executives now emphasize growth, and Gen AI has now become central to achieving this ambition (Fig. 1).

Overcoming challenges and managing risks

As companies accelerate Gen AI adoption, they must navigate key risks that could impact success in 2025.

The most pressing concerns include:

• Cybersecurity
• Economic downturns
• Talent retention
• Regulatory compliance
• Shifting customer expectations

While factors such as geopolitical instability, competitive threats and intellectual property leakage remain on the radar, they are considered secondary to more immediate business risks.

To successfully scale Gen AI, organizations must establish a robust foundation for AI, which encompasses the following elements:

• Strategy and leadership: Aligning AI initiatives with business goals
• Organizational and talent readiness: Reskilling employees to work alongside AI
• Ethics and compliance: Addressing AI governance and regulatory requirements
• Technology enablement and AI integration: Embedding AI in business processes
• Data management and architecture: Ensuring high-quality data to fuel AI systems

In addition, as companies are scaling Gen AI and reimagining work, they must start addressing other top concerns, such as process complexity, data quality, technology complexity, change management and the challenge of setting realistic expectations.

Enterprise approaches to AI adoption vary widely. According to The Hackett Group’s study, most organizations are using one of the following four models (Fig. 2):

• 34% of organizations employ a business-led strategy, where AI delivery teams report to the CIO
• 30% have chosen a centralized AI governance model
• 13% have embed AI delivery outside of IT
• 12% have integrated AI teams directly within business units

Regardless of the model, achieving meaningful results requires addressing operational complexities and aligning AI initiatives with enterprise-wide goals.

Unlocking the value of Gen AI

Executives are already seeing tangible benefits from Gen AI, including improvements in quality, productivity and customer and employee experiences, as well as reductions in operating costs and full-time equivalent (FTE) requirements. While most organizations are reporting incremental gains – typically up to 25% improvement – a select few have achieved transformative breakthroughs of 40% or greater (Fig. 3). These results demonstrate AI’s potential to revolutionize industries when effectively implemented.

However, organizations must address significant challenges to realize the full benefits.

These challenges include:

• Process and technology complexity: Ensuring seamless integration with existing systems
• Data quality concerns: Maintaining reliable and accurate data sources
• Defining and delivering on expectations: Establishing realistic targets and tracking progress

Interestingly, executives are now reporting less concern about obstacles to securing investment or winning leadership support – an indication that the focus has now shifted from experimentation to execution. With Gen AI now a central pillar of business transformation, companies must refine their strategies to drive measurable impact.

Scaling Gen AI: Key actions for 2025

Organizations poised to scale Gen AI in 2025 must rethink traditional operating models. Simply incorporating AI into existing frameworks will not suffice – businesses must reshape processes to unlock breakthrough value.

Here are the key areas of focus:

1. Pivot from experimentation to scaling AI.

Enterprises that continuously evolve their Gen AI capabilities achieve greater business value.

To sustain momentum:

• Move beyond reactive use case reviews.
• Involve leadership early to identify productivity, quality, customer and cost-savings benefits.
• Engage finance teams to establish realistic expectations and benchmarks.
• Track progress using defined spending and staffing levels.

2. Embrace co-intelligence and enterprise-wide AI adoption.

Gen AI is transforming work by enabling human–AI collaboration.

Businesses should:

• Foster a culture of co-intelligence in which humans and AI work synergistically.
• Reimagine processes to maximize AI’s potential.
• Involve domain experts to identify high-impact opportunities.
• Accelerate platform modernization to leverage AI-native capabilities.

3. Tackle complexity and improve time to value.

Complexity can slow AI adoption.

To mitigate this loss of momentum:

• Prioritize processes that deliver the highest impact.
• Identify and eliminate complexity using benchmarks and best practices.
• Address data quality issues proactively.
• Focus on readiness rather than perfection.

4. Invest in talent readiness and change management.

A skilled workforce is essential for AI success.

Organizations must:

• Redefine employee development programs to align with AI-driven work.
• Provide Gen AI training to upskill teams.
• Support key employees in adapting to AI-assisted and AI-autonomous tasks.
• Encourage collaboration between employees and AI agents to enhance productivity.

It’s time to reimagine work

The urgency to integrate Gen AI into business operations has never been greater. This presents business leaders with a clear imperative. As they take up this high-priority call to action, however, they must also take on the related challenge mentioned briefly above: they must reimagine their work, workforce, performance and competitive advantage with Gen AI. They must determine where Gen AI will assist human work, where it will augment human work, and where it will act autonomously.

Gen AI is no longer a remote possibility – it is now an immediate imperative. Organizations that act decisively now at the outset stand to gain a significant competitive edge, while those that hesitate risk playing catchup, or even being left behind altogether.

While AI adoption comes with risks, these challenges are manageable with the right strategies in place. In today’s fast-evolving competitive landscape, failing to act is the greater hazard. But an organization failing to rethink and reimagine work, the workforce, performance and competitive advantage while scaling Gen AI is the greatest risk of all.

Businesses that meet the challenges and embrace structured ideation, strategic use case development and disciplined implementation will seize new opportunities and stay ahead of the competition. Are you ready to scale Gen AI and unlock its full potential?

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