Presented by BCG
The C-suite recognizes the vast potential of generative AI, yet many remain hesitant to fully embrace it. Currently, only 6% of companies have trained over 25% of their workforce on generative AI tools. Two-thirds of executives surveyed anticipate it will take at least two years for AI and generative AI to evolve beyond the hype. Boards and executive teams are asking crucial questions: How does this technology function, and how will it transform business operations?
“We’re transitioning into a phase where companies are focused on delivering tangible impact,” explains Matthew Kropp, CTO and managing director of BCG X, the technology design unit of Boston Consulting Group. “Clients are investing millions to fundamentally change their operations. While we’re yet to see substantial value realized, progress is being made.”
However, mastering the technology is only one aspect of unlocking generative AI's full potential. Organizations are beginning to view generative AI not simply as a tool provided to employees but as an opportunity for transformative change. This requires dissecting employee processes, functions, and roles to identify where generative AI can alleviate monotonous tasks while enhancing meaningful human work.
Equally significant is addressing the cultural shift required to transform potential employee resistance or fear into enthusiasm. AI adoption is challenging, not only because it's new but also because employees need to feel motivated to learn and effectively utilize these tools.
“As companies begin to experiment with resolving pain points and driving real impact, they will encounter employee resistance for various reasons,” Kropp notes, citing hesitance to adapt to new work methods or fears about job security.
Identifying Business Opportunities and Securing Employee Buy-In
According to Kropp, every organization has key opportunities for improvement, but those might not be the best starting points.
“For instance, optimizing a large call center or refining a multi-billion-dollar marketing strategy presents significant opportunities. However, there are countless smaller opportunities in everyone's daily tasks.”
Engaging the entire organization through education is crucial for managing this cultural shift. Providing access to tools like Enterprise ChatGPT, providing training, and encouraging employees to rethink their workflows is vital.
“Employees need to understand that the goal is to enhance their roles, increasing job satisfaction and engagement.”
Encouraging grassroots ideation allows employees to explore the technology's possibilities and understand that it can reduce their workload, giving them more time to focus on the aspects of their jobs they enjoy.
“Minimizing employee toil while maximizing job satisfaction is essential. Identify work processes, determine where pain points exist, and automate those areas,” Kropp advises.
Recognizing that generative AI cannot replace uniquely human attributes such as creativity, diverse thinking, and relationship-building is fundamental.
For example, a financial institution with over 12,000 engineers is leveraging GitHub Copilot, a generative AI tool that assists with coding. Their implementation strategy focuses not just on basic usage training but also on showcasing how the tool can streamline tedious tasks, allowing engineers to focus on more rewarding aspects of their job.
“Generative AI excels at automating repetitive coding tasks, which excites engineers as it enables them to dedicate more time to creative problem-solving,” Kropp highlights.
Incorporating Joy into AI Strategies
BCG has developed the ADORE framework as a roadmap for successful AI implementation while enhancing employee well-being. This framework can be applied broadly across the organization or within specific teams to reengineer processes.
- Aim for Outcomes: Define clear objectives for integrating AI into business processes, such as enhancing customer satisfaction or reducing costs.
- Diagram Status Quo: Map out each step in the targeted process from beginning to end.
- Optimize for AI: Evaluate each step to determine which aspects are tedious and which are enjoyable, deciding what should be automated and what should remain human-driven.
- Redesign the Process: After identifying the areas where generative AI can add value, redesign the process, whether by automating specific tasks or rethinking the entire workflow.
- Ensure Outcomes: Establish metrics to measure performance, ensuring the organization meets its objectives while enhancing employee engagement and satisfaction.
The Importance of Experimentation
Kropp emphasizes that large-scale applications, such as improving call center efficiency or accelerating software development, are just the beginning. Significant advancements are also seen in AI-driven knowledge management and its application across various sectors.
“Continuously exploring opportunities is essential to realize the lasting, positive changes that AI can deliver,” Kropp asserts.
Organizations are witnessing engineers adapt new workflows with AI support, biopharma firms are shortening R&D timelines, and consumer product companies are innovating new sales channels.
“To instigate real and lasting change from the top, it's critical to unearth significant objectives and understand how generative AI will reshape the company. Organizations must actively engage in experimentation and invest in developing applications while ensuring that employee engagement remains at the core of their generative AI initiatives,” Kropp concludes.
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