How Enterprises Can Successfully Implement AI Copilots

AI copilots gain traction in organizations: Forrester’s research reveals a surge in AI copilot adoption, with 51% of global information workers reporting their organizations are embracing solutions like Microsoft Copilot for Microsoft 365 and ChatGPT Enterprise.

• Despite widespread adoption, organizations are struggling to quantify the return on investment (ROI) for AI copilots, creating a dilemma for leaders.
• The challenge lies in balancing the potential future benefits of generative AI (genAI) against the difficulty of measuring immediate results.

A pragmatic approach to AI copilot implementation: To resolve the genAI business case conundrum, organizations need to address four key areas: benefits, adoption, funding, and responsibility.

• Benefits: The immediate payoff of AI copilots starts with improved employee experience, which is crucial for driving productivity gains.
• Adoption challenges stem from employees struggling to master new technologies, potentially leading to diminished productivity or outright rejection.
• Funding for AI copilots often falls to tech leaders, but the report suggests that corporate priorities should be backed by corporate funding.
• Responsibility for successful implementation requires a collaborative team approach, involving various stakeholders across the organization.

Understanding the true benefits of AI copilots: Leaders must recognize that the path from implementing AI tools to realizing productivity improvements is not immediate and requires significant effort.

• The focus should be on human factors such as employee experience, collaboration, and culture to ensure successful integration of AI copilots into daily work.
• Organizations need to be patient and understand that there is a delay between launching AI tools and seeing tangible productivity gains.

Overcoming adoption hurdles: Successfully implementing AI copilots requires a human-centered approach and comprehensive support for employees.

• Many employees lack the understanding, skills, and ethical awareness necessary to use genAI effectively.
• Organizations should focus on human-centered design, proper employee training, process change, skills development, and continuous support to address adoption challenges.
• Misconceptions about genAI are common, even among decision-makers, highlighting the need for education and awareness programs.

Navigating funding challenges: The report outlines key practices to guide budget conversations for AI copilots, recognizing that funding models may vary based on the type of copilot being implemented.

• General-purpose copilots available to all knowledge workers should be funded from corporate budgets.
• Expert systems integrated into practitioner workflows may be funded from departmental or operations budgets.
• Task-specific copilots, such as those used by contact center agents, should be funded from operations budgets.
• While IT can administer these budgets, they shouldn’t be expected to cover the new costs entirely.

Creating a collaborative ecosystem: Successful implementation of AI copilots requires a diverse team of stakeholders working together.

• The traditional IT + business + operations team model needs to be expanded to include domain experts, ensuring genAI models make valid intellectual contributions.
• Data, AI, HR, customer experience (CX), employee experience (EX), and learning and development leaders should also be involved in the planning and implementation process.
• Organizations are encouraged to conduct workshops that bring together this “village” of stakeholders to develop a comprehensive copilot strategy.

Looking ahead: The evolving landscape of AI copilots: As organizations continue to grapple with the challenges and opportunities presented by AI copilots, several key considerations emerge for future success.

• The focus on employee experience and adoption will likely become increasingly important as organizations seek to maximize the value of their AI investments.
• Developing more sophisticated methods for measuring ROI and productivity gains from AI copilots will be crucial for justifying continued investment and expansion of these technologies.
• As the AI landscape evolves, organizations may need to remain flexible in their approach, adapting their strategies to accommodate new developments and emerging best practices in the field of AI copilots.