From Pilot to Scale: Building the GenAI-Ready Organization - TMG (original) (raw)

Introduction

While GenAI today is in the public eye, early forms of AI have influenced the workplace for decades. AI appeared in the 1950s, with more practical applications emerging thirty years later. With advances in machine learning and natural language processing, AI’s role expanded. Most remember when GenAI took center stage in late 2022, with ChatGPT capturing the world’s attention. According to OpenAI, more than one million people signed up in just five days.

The debut of GenAI technologies introduced an innovative way to reimagine how work gets done. Across sectors, C-suite leaders began to recognize GenAI’s potential to revolutionize industries— some believe that it could become as ubiquitous as electricity.1 The same leaders are also asking critical questions: What is GenAI truly capable of, and what might it replace? Could it create like humans do? Could it potentially harm without humans involved?

Today, the broad interest in GenAI persists, filled with potential as well as complexity. Rapid advancements challenge companies to quickly find advanced business applications, from new product development to process efficiencies. Relatedly, leaders also have a responsibility to ensure GenAI is used responsibly and ethically. On the other hand, the rapid development of data centers is now at the top of environmental concern lists, while the entry cost for companies to adopt GenAI at scale is proving restrictive.

It is also possible that the early hype over GenAI is losing some momentum. Recent research suggests that while 97% of executives feel an urgency to adopt AI, employee enthusiasm has dropped 20% in the US.2 Now, business leaders are winding down two years of pilots, and 60% of organizations are not yet developing an enterprise approach to GenAI.3

GenAI as a transformation imperative

Is 2025 the year when GenAI adoption proves itself, or not?4 Companies that have successfully run pilots are at a crossroads— two years of experimentation are giving way to the need to scale GenAI to show returns.5 Scaling GenAI brings practical challenges that take time to address, including technical complexity, data requirements, regulatory compliance, and high costs.

Another major hurdle to scaling GenAI is often overlooked: ensuring organizations are ready to adopt new approaches to how they work. Without a deliberate effort to prepare the organization for change, scaling GenAI risks becoming a technical project that lacks engagement from individuals critical to driving performance. The challenge is not just about scaling technology; it’s about scaling new ways of working.

C-suite leaders can start today by preparing a GenAI-ready environment. Proven practices from previous transformation efforts, while accounting for the unique needs of GenAI, can serve as a blueprint. This means designing an integrated approach that focuses on building (i) a smart operational and governance foundation, (ii) leadership capabilities focused on GenAI, and (iii) an insightful and engaging communications strategy. This approach will position companies to lead the change more effectively and shape GenAI practices for the long term.

1. Build a smart operational and governance foundation

Any successful business transformation needs strong strategic alignment, governance, and executive sponsorship. With GenAI, that foundation must include (i) access to integrated data sets and (ii) identifying and prioritizing the processes and operations that will benefit from GenAI. Doing the groundwork to scope changes for the future state is essential to set the stage.

From there, bringing teams along in a structured way helps scale adoption. Whether inspired by business movements like Lean, design thinking, or change management frameworks, organizations looking to scale GenAI can start now by building an operating foundation with governance and management systems that can adapt well to the rapidly changing environment.

Strategic opportunities:

Case in point: CHROs from top companies—including GE, Intel, Workday, and IBM—defined a crossfunctional framework for organizations to champion the responsible use of AI while promoting alignment to business goals and organizational purpose. The principles they outlined recognized AI’s potential to impact how work gets done across the enterprise while promoting optimal use of resources to drive the greatest impact.8

2. Build leadership capabilities focused on GenAI

Business leaders recognize that GenAI has the potential to reshape the future of work across nearly every sector. The World Economic Forum estimated that 50% of the global population needs new skills to meet shifts in demand driven by new technologies.9 Relatedly, in a recent Gallup survey, three-quarters of Americans expressed concern that AI will reduce the number of available jobs over the next decade.10 While it is early for most companies to have definitive answers, organizations can start by preparing leaders to adapt to a GenAI-focused transformation and, in turn, guide their teams.

Strategic opportunities:

Case in point: Dell Technologies has made workforce readiness for AI a public priority, naming its first Chief Artificial Intelligence Officer to lead these efforts. The role’s mandate includes rolling out tailored training programs for 120,000 employees, ensuring they are equipped to navigate AI’s growing influence. The training is customized by role, offering introductory courses for nontechnical employees and advanced coursework for data science professionals. This strategic approach ensures that every team member, regardless of their expertise, is prepared to contribute meaningfully to Dell’s AI-driven transformation.14

3. Build an insightful and engaging communications strategy

When uncertainty is high, effective and consistent communication plays a crucial role. In the disruptive world of GenAI, strong communication approaches are even more critical. According to Gallup, while 93% of CHROs report using AI in their organizations, only 33% of employees are aware of these efforts, and 15% feel their organization has communicated a clear strategy for integrating AI into business practices.15

Rather than focusing only on certainty, leaders can promote adaptability when considering the practical realities of GenAI at scale. Creating new business narratives that share the core idea of the GenAI transformation while conveying how it relates to the organization’s strategy and vision helps teams acknowledge the unique journey ahead. Similarly, using structured change communication practices to share learnings, milestones, and accomplishments helps educate and build confidence in what’s possible.16

Strategic opportunities:

Case in point: Asana demonstrates the power of sharing success through intentional communication. The company hosts show-and-tell sessions and uses an AI-focused Slack channel to encourage employees to share their AI experiments and innovations. These platforms enable employees to learn from one another and reuse successful examples, creating an environment where collaboration drives adoption. By spotlighting individual contributions and creating opportunities for knowledge exchange, Asana has embedded sharing as a cornerstone of its AI communication strategy.18

Scaling for impact: The GenAI advantage

GenAI is already reshaping industries. For companies to fully benefit, leaders know they will need to move beyond experiments, backed by strong technology and employees ready to use it. By starting to build the GenAI-ready organization now, teams will be ready to expand pilot efforts to drive enterprise impact. Using an integrated transformation approach— built on smart operational, leadership development, and communication strategies—ensures the focus stays on what people need, how they work, and what’s possible.