AI In the Workplace – AWA Study Group

The group concluded that AI poses a more complex challenge than previous technology shifts. It requires a science-based, integrated change management approach across three interconnected dimensions: People & Capability, Organisational Processes, and Safety & Reputation.

From this, the Methodology for Mobilising AI was developed, ensuring systematic yet flexible adoption:

1. Raise AI Awareness, Identify Opportunity Areas & Assess Readiness: This initial step involves building AI awareness among leaders, ensuring they understand AI, its differences from automation and strategic opportunities. It includes assessing where AI can benefit the organisation, aligning with strategic goals, and conducting a high-level AI readiness assessment.
2. In-depth Opportunity Review This phase involves a comprehensive readiness review, evaluating technical elements, innovation culture and employee attitudes. It includes a skills audit to assess workforce capabilities and predict AI’s impact on tasks, skills (e.g., “fusion skills” like intelligent interrogation, human discernment and training AI systems), and roles. The AWA AI DNA Profiler Tool is used here to gain insights into how AI may influence job functions and workforce planning, guiding the identification of target use cases.
3. Assess Tech Readiness:: Once initial opportunities are identified, a more thorough technical evaluation is performed to determine if the organisation possesses the right data in the right condition, along with the necessary technological infrastructure, to deliver the prioritised use cases effectively.
4. Building AI Foundations: This step involves converting identified use cases into practical AI prototypes and pilot projects. It emphasises hands-on experimentation, enabling employees to interact with AI tools, test hypotheses and enhance AI applications before full-scale implementation. Organisations should provide AI co-pilots, prompt libraries and technical training programs to support this experimentation.
5. Implementation and Ongoing AI Integration: AI deployment is regarded as a continuous journey. Successful implementation necessitates scaling AI applications throughout the organisation while nurturing a culture of ongoing innovation. Key enablers include showcasing successes, inspiring and supporting new AI ideas from employees, and establishing governance frameworks for assessing the value and safety of new applications.

This methodology, refined through the AWA Study Group’s collaborative insights, provides a practical roadmap for organisations to navigate the complexities of AI adoption, ensuring a strategic and sustainable transformation.

The AWA Study Group recognised that despite the significant opportunities AI presents, organisations frequently encounter substantial barriers during adoption. These challenges primarily stem from employee concerns and a general lack of understanding about AI’s true nature and capabilities. The integration of AI into working lives is likely one of the most profound changes individuals will experience.

Key barriers identified by the study group include:

• Fear of Job Displacement: This is a prevalent concern among employees, who often view AI integration as a major threat to their livelihoods and job security.
• Lack of Basic Digital Skills: Many employees lack the fundamental digital literacy required to effectively interact with and utilise AI tools, which significantly hinders widespread adoption and effective utilisation.
• Lack of Trust in AI and its Output: Skepticism arises from anecdotal views about AI, such as its perception as enabling “cheating” in educational settings, compounded by a broader lack of knowledge. This leads to doubts about AI’s reliability and accuracy, impacting user acceptance.
• Lack of Communication & Transparency: Insufficient or unclear communication from leadership can exacerbate fears and resistance, creating an environment of uncertainty and distrust within the organisation.
• Lack of Leadership Support: Without strong, visible support and clear guidance from senior leadership, AI integration efforts can be significantly hampered, as employees may not perceive it as a priority or a genuinely supported initiative.

The study group emphasised that overcoming these deep-seated barriers requires more than just technical solutions; it demands clear communication and effective change management to shift fear into curiosity and adoption.

The work of the AWA Study Group indicated that the effects of AI on organisations extend beyond the deployment of technology. It involves adjustments in work practices, decision-making processes, and organisational culture. The findings suggest that integrating AI is not limited to adopting tools, but includes changes in how roles are structured, tasks are carried out, and how organisations adapt to new forms of interaction between people and AI systems.

In this context, AWA developed the AI DNA Profiler in 2024 to examine how AI may affect specific job roles and functions. The tool is intended to offer insight into the nature and extent of change associated with AI integration.

The tool’s robust analysis is informed by several key factors, including:

• Proportion of routine/repetitive vs. complex tasks
• Degree to which human judgment is required
• Amount of data collection/processing and time spent on it
• Importance of academic or professional qualifications
• Level of predictability of work and tasks
• Level of emotional intelligence required
• Extent of manual work

Based on the detailed job information collected, the AI DNA Profiler generates two key outputs. First, it compares the role with reference profiles to estimate the potential influence of AI, resulting in a classification of expected outcomes.

Second, it provides an estimate of the time that may be saved or reassigned through the effective integration of AI into the role. This calculation, referred to as the “AI Time Dividend,” offers a data-informed projection of possible productivity changes and capacity shifts associated with AI use.

For more information regarding the AI DNA Profiler Tool, refer to the article on AI Impact Assessment.

The findings from the application of the AI DNA Profiler offer indicative insights rather than definitive conclusions, as the sample was relatively small (32 roles) and skewed by the type of participants who completed it. Nevertheless, some patterns emerged.

Many roles examined showed potential for AI to improve effectiveness by taking on certain repetitive or routine elements, particularly in jobs that combine daily tasks with the need for professional judgment and emotional intelligence. Roles with strong regulatory constraints, however, appeared more limited in the scope for AI application.

Importantly, while very few of the roles analysed appeared likely to be fully automated, automation of administrative and routine work could still have wider consequences. Efficiency gains that free up time for higher-value activities may also, when aggregated across organisations, lead to restructuring or reductions in headcount. This duality highlights the need for organisations to approach AI adoption with caution: it can enhance productivity and innovation, but it may also reshape workforce demand and job security.

The AI in the Workplace – AWA Study Group has provided a clearer perspective on how Artificial Intelligence is shaping organisational structures, processes, and ways of working. Its findings indicate that successful AI integration requires adjustments not only in technology but also in culture, workflows and decision-making practices. While AI will undoubtedly support human work by automating repetitive tasks, the efficiency gains it creates are also likely to lead to job displacement in some areas, as organisations restructure and reduce roles in response to these changes.

The tools and insights from the study group provide organisations with a practical framework for incorporating AI into operations, enabling more informed planning and gradual, structured adaptation.

To learn more about how AWA can support your organisation’s AI transformation journey, contact us today.