AI Transformation: Do your people have the AI skills they need?

Fujitsu / January 6, 2025

AI Computing Converging technologies Digital Transformation

AI is no longer a niche technology it has rapidly become key to transforming both organizations and the services they deliver. From automating content creation to revolutionizing customer service with intelligent chatbots, Generative AI is reshaping the business landscape and enhancing competitive advantage.

According to a 2023 report by McKinsey, Generative AI has the potential to add $4.4 trillion (about $14,000 per person in the US) annually to the global economy. Yet, as organizations rush to adopt AI technology a critical question arises “Do your people have the skills they need to get the most from AI and Generative AI?

Investing in upskilling and reskilling the workforce is a critical success factor in maximizing both the potential of AI in organizations and the return on investment from AI adoption.

The rise of Generative AI in the enterprise
The Generative AI skills gap
Enabling a Generative AI-skilled workforce
Measuring the ROI of Generative AI skills
Conclusion
Recommendations

The rise of Generative AI in the enterprise

The rise of Generative AI in the enterprise marks a transformative shift in business operations and strategy. By leveraging advanced machine learning algorithms, companies can now automate complex tasks, generate innovative solutions, and enhance decision-making processes. This technology not only drives efficiency but also fosters creativity, enabling organizations to stay competitive in a rapidly evolving market.

However, there is often a significant gap between the potential of Generative AI to benefit organizations and the ability of many organizations to fully realize that potential. This gap is largely due to a lack of the necessary skills among employees.

A recent study by Accenture found that companies with a strong focus on AI skills development saw a 25% higher return on AI investments compared to those that did not prioritize skills development. Underscoring the importance of building a workforce that is not just familiar with Generative AI but proficient in its application.

The Generative AI skills gap

The rapid advancement of Generative AI technology has outpaced the development of the skills required to use it effectively. According to a 2023 Deloitte survey, 65% of business leaders identified a lack of AI-related skills as the biggest barrier to adopting AI technologies, including Generative AI. This skills gap is particularly pronounced in the following areas:

1. Understanding AI Capabilities and Limitations: Employees need to understand what Generative AI can and cannot do to set realistic expectations and use the technology effectively. This requires technical knowledge and critical thinking skills to assess when and how to apply Generative AI.

2. Data Literacy: Generative AI relies heavily on data, and the quality of that data directly impacts the effectiveness of AI models. Employees need to be data literate, understanding how to collect, clean, and interpret data to ensure accurate inputs and relevant outputs.

3. AI Model Training and Fine-Tuning: Maximizing the effectiveness of pre-trained Generative AI models often requires fine-tuning to align with specific business needs. This involves adjusting the models based on organizational data and objectives.

4. Ethical AI Usage: The power of Generative AI comes with ethical responsibilities. Employees need to be trained in both the technical aspects of Generative AI and ethical considerations, including identifying and mitigating biases in AI outputs.

5. Cross-Functional Collaboration: Generative AI projects often require collaboration between multiple departments. Employees need strong collaboration skills to work effectively in cross-functional teams, communicating complex technical concepts to non-technical stakeholders and aligning AI initiatives with broader business objectives.

Enabling a Generative AI-skilled workforce

Addressing the skills gap in Generative AI requires a comprehensive strategy that includes upskilling existing employees, fostering a culture of continuous learning, and integrating AI literacy into the organizational fabric.

1. Upskilling and Reskilling Programs

One of the most effective ways to bridge the skills gap is through targeted upskilling and reskilling programs. These programs should be designed to cater to various levels of expertise within the organization:

• For Technical Teams: Offer advanced training in AI model development, data management, and AI ethics.

• For Non-Technical Teams: Provide foundational knowledge of AI, focusing on how Generative AI can be applied to their specific roles.

Example: A leading global bank launched an internal AI academy, training 2,000 employees in its first year, significantly boosting the organization’s AI capabilities.

2. Fostering a Culture of Continuous Learning

Generative AI and related technologies are evolving rapidly, and staying up to date is crucial. Organizations should foster a culture of continuous learning, where employees are encouraged to constantly update their skills and knowledge. This can be achieved through:

• Regular Training: Offering ongoing training programs and refresher courses to keep employees up to date with the latest advancements in AI.

• Learning Communities: Creating internal communities or forums where employees can share knowledge, discuss challenges, and collaborate on AI projects.

• Incentives: Providing incentives for employees to pursue AI certifications or advanced training, such as covering the cost of courses or offering bonuses for completed certifications.

3. Integrating AI Literacy into the Organizational Fabric

AI literacy should not be confined to a few specialists within the organization; it should be embedded into the organizational fabric. This can be done by:

• Including AI Competencies in Job Descriptions: Ensuring that AI-related skills are included in job descriptions, not just for technical roles but across the organization.

• AI in Onboarding Programs: Incorporating AI literacy into onboarding programs for new employees to ensure that all staff members, regardless of their role, have a basic understanding of AI and its applications.

• Leadership Development: Equipping leaders with AI knowledge so they can make informed decisions about AI strategy and investments. Leadership programs should include modules on AI’s impact on business, ethical considerations, and how to lead AI-driven transformation.

Measuring the ROI of Generative AI skills

Investing in Generative AI skills is not just a cost center; it is a strategic investment with measurable returns. Organizations that prioritize AI skills development are more likely to see tangible benefits, including:

• Increased Efficiency: Employees skilled in using Generative AI can automate routine tasks, freeing up time for more strategic work.

• Enhanced Innovation: A workforce that understands and can leverage Generative AI is better positioned to drive innovation.

• Improved Decision-Making: Generative AI can provide insights that lead to better decision-making. When employees understand how to use these tools effectively, they can make data-driven decisions that enhance business outcomes.

Conclusion

Generative AI offers immense potential, but the benefits and return on investment hinge on having a workforce skilled in leveraging AI technology. Organizations that invest in upskilling and reskilling their workforce will gain a competitive advantage in an increasingly AI-driven world.

Recommendations

Fujitsu has successfully delivered over 2,000 AI projects globally. Contact Fujitsu to learn how we can help your organization maximize the potential of AI.

Nick Cowell

Principal Consultant & Fujitsu Distinguished Engineer / Technology Strategy Unit/ Fujitsu

Nick is a technologist and futurist with extensive experience in hardware, software, and service development, having previously worked for leading technology providers across the USA, Europe, and Oceania.