GenAI coaches: Pioneers of intelligent work integration

Learn more about the transformative role AI coaches play in driving efficiency through enterprise AI

By Tamarah Usher, Julie Cline, and Marco Kilongkilong

Generative AI is transforming the future of work, offering impressive potential yet facing cautious adoption. Executives and employees grapple with concerns ranging from trust issues and skill gaps to data challenges, slowing its integration into the workplace.

A strategic approach is crucial to unlock this technology’s full promise. Central to this strategy is the AI coach, whose role is pivotal in steering organizations through these complexities and driving successful generative AI adoption from the ground up. We will explore how AI coaches become the linchpins of change, guiding teams toward innovative futures.

Why are organizations struggling with general-purpose generative AI?

1. Uncertainty and governance: Rapid advancements in GenAI technology create uncertainty, raising concerns about risk and causing hesitation in adoption.
2. Trust and perspective gaps: There is a divide between executives who see GenAI’s potential benefits and employees who fear job displacement. This conflict undermines trust and slows adoption.
3. Skill gaps and training needs: Many executives recognize the need for workforce reskilling to use GenAI effectively, but few employees have access to adequate training, delaying effective integration.
4. Accuracy and reliability: GenAI’s inconsistent outputs, including inaccurate or “hallucinated” data, challenge its reliability and trustworthiness.
5. Change management and reskilling: Effective integration of GenAI into work processes requires substantial skilling and adept change management, areas where many organizations struggle.

As a relatively new technology, GenAI is still evolving rapidly. Focusing on more general-purpose applications could allow organizations to benefit from this technology while it matures, rather than investing heavily in bespoke solutions that may become obsolete.

Rethinking use cases for generative AI

Despite the broader challenges, organizations are expected to employ a top-down approach for some specific use cases. This includes significant investments to achieve targeted outcomes, enhance AI technology enablers, and refine data maturity and pipelines. However, a narrow focus on traditional use case approaches may need to be revised when applied to generative AI. This is due to several unique characteristics of the technology:

Broad applicability

Generative AI’s wide-ranging potential across various tasks and industries makes it difficult to encapsulate its capabilities in limited use cases. Its diverse applications span from content generation to complex decision-making.

Dynamic adaptability

Unlike static technologies, generative AI continually learns and adapts, taking on new roles as it processes more data. This evolving nature challenges the fixed framework of traditional use cases.

Enhanced collaboration

Generative AI excels in partnership with humans, augmenting human capabilities rather than merely automating tasks. This synergy often defies the narrow confines of predefined use cases, as the technology enhances human work in fluid and dynamic ways.

Transformative impact

Focusing solely on specific use cases might obscure generative AI’s potential to transform business operations and industries. This transformation goes beyond simple task execution to revolutionize workflows and organizational structures.

Adapting to the reality of dynamic and exponential AI transitions

Generative AI will continue to profoundly impact work as we know it by embedding AI agents — intelligent, adaptive collaborators — into daily workflows. As these agents become integral to business processes, employees transition from individual contributors to leaders who manage and guide AI-driven activities.

To prepare for this next step change in the future of work, employees must become adept today at continuously engaging with AI, integrating it into every aspect of their daily tasks. This requires them to learn new “AI literacy” skills, enabling them to communicate with AI effectively, provide targeted feedback, and critically assess AI-generated outputs. This ongoing interaction blurs the traditional roles of user and tool, making it essential for employees to continuously update their skills to stay adept at directing AI toward optimized business outcomes.

Organizations must adapt by restructuring their processes and cultural norms to support this evolving human-AI collaboration. This continuous transformation in the workplace demands immediate attention to skill development and workflow adjustment to fully leverage AI’s potential for innovation and productivity.

Elevating the role of the AI coach in AI organizational transformation

AI coaching has become indispensable as organizations tackle the complexities of integrating generative AI. Drawing parallels from the success of Agile coaches in easing the adoption of Agile methodologies, AI coaches are pivotal in ushering in the new dynamics of work enabled by generative AI.

AI coaches act as mentors, trainers, and facilitators, equipping organizations with the essential skills, mindset, and cultural adaptability to maximize the benefits of generative AI. They engage deeply with employees to foster trust, provide on-the-job training, and mitigate concerns related to job displacement. By promoting a continuous learning and adaptation culture, AI coaches are instrumental in navigating the challenges of broad GenAI adoption, unlocking significant value and efficiency gains.

AI coaches in practice:

1. Workflow observation: AI coaches observe team workflows to pinpoint optimal opportunities for GenAI augmentation.
2. Process optimization for AI use: Coaches assist in breaking down processes for optimal use with GenAI, focusing on standardization and improved prompting to bring consistency to outputs.
3. Documentation and assessment: Coaches document repeatable tasks and AI effects, assessing efficiency changes and workflow impact to support strategic decisions.
4. Building AI excellence: Enhance prompting skills and ethical AI practices through focused, on-the-job learning that also prioritizes creating a supportive environment for experimentation.
5. Crafting the value story: Coaches estimate efficiency gains, risk reduction, standardization, and quality improvement through AI integration to articulate GenAI’s organizational value.

Implementing a generative AI coaching program

Maximize your workforce’s potential by providing the support they need to excel in the evolving work landscape. Here are key strategies to ensure your AI coaching program is complete and poised for tremendous success, paving the way for a future where technology and talent thrive together.

AI coaching program success:

1. Program development and coverage: Develop the AI coaching program to align with the organization’s specific needs and objectives, prioritizing coaching coverage and intensity.
2. Performance metrics: Establish clear metrics and KPIs to evaluate the AI coaching program’s effectiveness and impact on GenAI adoption.
3. Learning and collaboration: Use a guild model to connect coaches, encourage learning, and iterate the program based on shared insights and evolving organizational goals.
4. Cross-departmental collaboration: Encourage departments to collaborate and share insights and strategies, fostering a more integrated approach to AI adoption.
5. Staying current: Ensure the coaching program is equipped to keep current with the latest AI developments and practices.

While the path to widespread adoption of generative AI in the workplace is not without challenges, organizations that embrace the role of AI coaching and follow success guidelines are well positioned to navigate this journey.

By investing in developing AI skills, fostering trust, and promoting a culture of continuous learning, organizations can harness the power of generative AI to drive innovation, productivity, and growth in the years ahead.

Slalom is a fiercely human business and technology consulting company that teams with leaders who expect more. So we bring more.