PETER FRANKE-MATTHECKA: How organisations can help staff catch the AI wave

Artificial intelligence (AI) implementation is advancing rapidly, but people-centric aspects such as skills development, change management and cultural readiness are lagging behind, risking the expected return on investment from AI investments.

To bridge this gap, organisations must establish an organisational change programme to address mindset shifts and leverage AI capabilities in familiar legacy systems. These complementary strategies can encourage utilisation, build trust and ensure organisations do not lose the strategic advantage driven by AI.

In its 2024 annual global study, the IBM Institute for Business Value found that 64% of CEOs surveyed believe succeeding with AI will depend more on people’s adoption than the technology itself. The study highlights that CEOs recognise the significant challenge generative AI poses, with nearly two-thirds stating that their organisations must leverage technologies evolving faster than employees can adapt.

Only 31% of workers responding to PwC’s Global Workforce Hopes & Fears Survey 2023 expected generative AI to increase their productivity and efficiency at work in the next five years. To build trust, they suggest starting with transparency and inviting employees to play an active role in reinvention. Such findings underline that for successful AI adoption, organisations need to create a culture supporting innovation and experimentation.

In 2022 a business strategy consultant expressed concern to the author that despite their client commencing a five-year technical road map their workforce would not transition in time. Due to the rapid advancements in AI technologies, people readiness is even more at risk.

Many employees do not understand AI and are unsure how it will affect them, leading to fear, resistance and obstructiveness. This issue extends beyond end users to IT staff and governance personnel uncomfortable with the new risks.

Resistance

To address these challenges organisations should establish an organisational change programme, applying proven mindset change techniques, paving the way for the adoption of new cultural values about AI. Leadership must continuously communicate and reinforce these values, including the future role of people, data-driven decision-making, and encouraging experimentation. Adjusting organisational design to align structures and functions with new work approaches is crucial. Equipping workers with new competencies is also essential for adopting AI-driven processes.

While the longer journey of organisational change is under way, there is an immediate, low-complexity opportunity to introduce AI into the organisation by leveraging legacy systems recently updated with AI capabilities. This approach can reduce resistance, streamline learning and demonstrate immediate value, making the transition to AI-enhanced operations smoother. The following are reasons why legacy systems provide an excellent platform for gradual AI adoption:

• Familiarity and comfort. Users already acquainted with legacy systems experience a shorter learning curve. Copilot in Word and Excel leverages generative AI to craft new content from input prompts, aiding tasks such as drafting, summarising, rewriting and creating data visualisations. Large language models generate text that resembles human writing and analyse data, so are capable of producing novel content and insights from data sets provided.
• Seamless integration. AI features can enhance existing workflows seamlessly. Google Workspace’s Smart Compose and Explore features, integrated into Gmail and Google Sheets, enhance productivity. For instance, Smart Compose in Gmail smartly completes your emails.
• Incremental implementation. AI can be incrementally introduced, starting with simple features such as predictive text to build trust before advancing to more complex capabilities. Adobe Sensei’s AI-powered features started with fundamental automation and later expanded to uncover insights, discern effective strategies and initiate campaigns with a greater likelihood of success.
• Proven success stories. Salesforce Einstein’s integration for predictive analytics about customer behaviour exemplifies tangible benefits and return on investment. By showcasing the probability of a lead converting into a sale or a customer churning, such case studies mitigate adoption resistance.

Addressing the human aspect of AI adoption is crucial for realising its full potential. By leveraging familiar legacy systems and implementing robust organisational change programmes, organisations can bridge the gap between technology and people, ensuring a smoother transition and unlocking AI’s strategic advantages.

• Franke-Matthecka specialises in workforce readiness for the Future Workplace.