The biggest challenge with any technology is getting people to use it well, and AI is no different.
Even though technical discussions often dominate AI implementation programs, the human aspect of change management is equally crucial. When shaping use cases and developing solutions, teams need to make conscious decisions about how far they want to stretch the adoption effort for users.

The AI transformation is unlikely to happen with a big bang, so there are levels of Human and machine collaboration companies need to consciously manage, as the image above illustrates. And even if it is the best solution, it might not be the right time to release it.
A few key questions to ask are:
How many other initiatives and software are employees being asked to adjust to?
What is the level of experience and understanding of AI and AI-powered solutions?
What is the current state of mind they are in, i.e., firefighting or growth?
Climbing on the ladder of AI working side by side with employees needs to be planned and enabled, to ensure the right thing is built, in the right order, and in a way that users can recognise and be ready for.
Upskilling at Scale: Amazon's Upskilling 2025 program

When Amazon recognised the need to prepare its workforce for AI and automation, it launched a $700 million upskilling program. The initiative, aimed at training 100,000 employees in high-tech skills, demonstrates the scale of change management required for successful AI integration. Additionally, Amazon has launched apprenticeships in the UK to ensure they have incoming talent already trained to follow a new tech-enabled career path.
Key takeaways:
Invest in comprehensive AI literacy programs for all levels of the organisation, differentiating technical from non-technical users.
Create cross-functional teams to drive AI adoption and share best practices.
Develop clear communication strategies to address employee concerns and highlight AI's benefits.
Enable employees to experiment and adapt.
Lead by example.
Successful AI integration requires more than just technical expertise; it demands a workforce that is prepared, willing, and able to embrace AI-driven change. By prioritising change management, enterprise leaders can ensure their AI initiatives have the human support necessary for long-term success.
Companies that jump straight into replacing humans will be forced to step back - just look at Elon Musk's approach to automation in his Tesla assembly line.
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