Why your team fails to use GenAI effectively (and how to change it)

Designing an effective GenAI learning program is a strategic imperative for organisational leaders in the era of artificial intelligence, writes Dr Gleb Tsipursky.

In today’s rapidly evolving technological landscape, generative artificial intelligence (GenAI) has emerged as a transformative force, reshaping industries and redefining operational paradigms. It offers unprecedented opportunities for organisations to enhance efficiency, innovation, and competitiveness. For organisational leaders, the imperative is clear: to harness the full potential of GenAI, a meticulously crafted learning program is essential. Such a program must address the diverse needs of the workforce, ensuring that employees are not only knowledgeable but also proficient in applying GenAI tools within their specific roles. As GenAI adoption accelerates, training programs must prioritise relevance, accessibility, and equity to ensure maximum impact.

Tailoring learning content to specific roles to use GenAI

A universal training approach often falls short in addressing the unique requirements of different roles within an organisation. To maximise the impact of GenAI, it’s crucial to develop role-specific learning modules that align with the distinct responsibilities and expertise levels of employees. This targeted strategy ensures that each team member acquires relevant knowledge and skills pertinent to their function, driving both efficiency and innovation.

For instance, in a law firm setting, attorneys might focus on leveraging GenAI for legal research, contract analysis, and drafting legal documents, while paralegals could concentrate on automating routine administrative tasks. Similarly, in the healthcare sector, clinicians might utilise GenAI for diagnostic insights, while administrative staff employ it for scheduling and patient communications. Personalised and role-based learning has traditionally been challenging to implement at scale, but GenAI offers solutions that enable organisations to overcome these barriers. By tailoring training to specific job functions, organisations foster greater engagement, ensuring employees see direct applications of their learning.

Balancing theory with practical application to use GenAI

While understanding the theoretical foundations of GenAI is important, the true value emerges from practical application. Incorporating hands-on exercises and real-world case studies into training programs bridges the gap between abstract concepts and day-to-day practice. This experiential learning approach enables employees to apply GenAI tools effectively, fostering both confidence and competence.

An effective GenAI learning program must be accessible and inclusive, catering to employees with varying technical backgrounds and learning preferences. Offering training materials in multiple formats – such as video tutorials, written guides, and interactive simulations – ensures that all employees can engage with the content effectively. For example, some employees may prefer step-by-step video demonstrations, while others might favour detailed textual instructions.

Beyond delivery methods, inclusivity extends to addressing potential biases in training materials and the GenAI tools themselves. Research from Harvard Business Review underscores that AI systems can inadvertently perpetuate bias if not carefully monitored. Organisations should conduct regular audits of their training content and AI algorithms to promote fairness and equity. Partnering with external experts or adopting frameworks like the Responsible AI approach from Microsoft can help organisations maintain high standards of inclusivity and ethics.

Inclusivity also means providing additional support for employees who may face barriers to learning, such as offering extra training sessions or creating peer mentoring programs. By prioritising inclusivity, organisations foster a learning environment where every employee feels empowered to develop their GenAI skills, enhancing organisational capability and morale.

Case study: A law firm’s GenAI transformation

A regional law firm recognised the strategic importance of GenAI in maintaining its competitive edge. To standardise knowledge and leverage AI’s potential, the firm asked me to help them launch a comprehensive learning program tailored to its diverse workforce. Attorneys focused on applications like legal research, drafting, and risk analysis, while paralegals and administrative staff concentrated on automating scheduling, data management, and communications.

The program’s cornerstone was its emphasis on practical application. Employees participated in workshops where they applied AI tools to real-world scenarios, such as automating the review of case documents or drafting responses to legal inquiries. Training materials were made accessible in various formats – video, interactive modules, and written guides – ensuring all staff could engage effectively.

Within six months, the firm observed significant improvements:

• Adoption rates of GenAI tools surged from under 20 per cent to over 85 per cent.
• Attorneys reported a 30 per cent increase in efficiency for document drafting and analysis.
• Administrative staff reduced time spent on routine tasks by 20 per cent, freeing them to focus on higher-value activities.

These results underscore the transformative potential of a well-designed GenAI learning program, demonstrating measurable benefits across multiple dimensions of organisational performance.

Overcoming common challenges

Despite its promise, implementing a GenAI learning program is not without challenges. One common obstacle is resistance to change, particularly among employees unfamiliar with AI technologies. Likewise, many employees suffer from automation anxiety, the fear that their skills may become obsolete. To address this, leaders should emphasise the tangible benefits of GenAI through clear communication and success stories of upskilling from within the organisation.

Another challenge is maintaining engagement throughout the training process. GenAI learning programs should incorporate gamification elements, such as quizzes and progress tracking, to sustain interest.

Lastly, organisations must allocate sufficient resources – both financial and human – to develop and sustain their training initiatives. Securing leadership buy-in is essential to ensure that GenAI training receives the necessary support and aligns with broader organisational goals, while managing risks.

Conclusion

Designing an effective GenAI learning program is a strategic imperative for organisational leaders in the era of artificial intelligence. By tailoring content to specific roles, balancing theoretical knowledge with practical application, and ensuring accessibility and inclusivity, organisations can empower their workforce to harness the full potential of GenAI. The success of these initiatives lies not only in enhancing individual capabilities but also in driving broader organisational transformation. As demonstrated by real-world case studies, a thoughtfully designed learning program can unlock significant efficiency gains, foster innovation, and position organisations as leaders in their industries.

Gleb Tsipursky, PhD, is the chief executive of hybrid work consultancy Disaster Avoidance Experts.