The secret to responsible generative AI adoption? Put people first, think beyond productivity—and don’t skip your ‘why for AI.’
The speed of generative AI adoption is breathtaking. We only need look at how ChatGPT achieved wide-scale adoption in under a year—the internet took 17—and the excitement for tools like Microsoft Copilots to put the power of AI at employees’ fingertips.
Yet the path to AI value in the workplace is less about flipping the switch on technology — and much more about people, upskilling and organizational change. The acceleration of Microsoft Copilot in 2024 will act as a catalyst for leaders to rapidly get across these strategic considerations.
So where do you start? How do you measure value? And what will generative AI look like in your organization?
#1 – Start with your people and prioritize training over technology
AI value doesn’t start with technology. It starts with what’s most important: people. Employees are clearly ready, with Avanade research showing that 95% of employees are optimistic about AI. And, contrary to the hyped fears that AI will replace humans, most leaders disagree that AI will take people’s jobs. In fact, nearly 10% expect to increase their headcount in 2024 as AI becomes more pervasive.
However, there is less confidence that people and processes are ready, with only 36% of CEOs feeling ready for AI adoption. Equally, 63% of leaders recognize that their employees will need to learn new skills to make the most of generative AI.
We recommend that you make upskilling a number one consideration in your AI roadmap. It’s something we prioritize through our School of AI, which equips our people with new skills such as “AI prompting”, that will become as ubiquitous as browsing the internet. The importance of education also held true in our experience as early adopters of Microsoft Copilot for Microsoft 365. Our teams universally acknowledged the need for comprehensive training, communication and transparency about what it can—and, just as importantly, cannot—do. We found that giving attention to training and ongoing support—including tailored approaches—improved people’s effectiveness whilst increasing confidence levels by 26%.
#2 – Value from generative AI goes beyond productivity
Unsurprisingly, productivity gains are top of mind as employees take mundane tasks off their to-do list. Teams at Avanade using Microsoft Copilot for Microsoft 365 reported significant productivity enhancements—up to 2-3 hours a day—by automating tasks such as drafting emails, generating reports, and summarizing notes.
But to understand the true value from AI, we recommend taking a more rounded view of how it helps people—and therefore the organizations they work in—be the best versions of themselves. For our teams using Microsoft Copilot for Microsoft 365, productivity was just the start:
· 52% saw a positive impact on the quality of their work
· 70% said they had a greater likelihood of fostering a creative approach to tasks
· 31% reported less cognitive fatigue
A further consideration is how you frame value for specific teams. People will be much more motivated to adopt new tools if they perceive the value in their specific context. As an example, with Microsoft Copilot for Sales our sellers reduced workload with a range of time-saving features. But the inspirational value lies in freeing up sellers to do what they love and do best: delighting clients by finding new ways to add value.
When you instill confidence in AI’s full potential—by showing how it will add value to specific roles or working styles—you drive buy-in with your people which leads to adoption, acceptance and advocacy. Equally, people will be more likely to trust AI if there is a robust feedback mechanism that allows teams to report issues, suggest improvements and experience ongoing improvements.
#3 – Don’t skip your ‘why for AI’
The best way to extract value from AI is to fully understand why you’re using it in the first place. This rests on how it aligns with your purpose and the desired outcomes that make your organization unique. If you don’t know your why, you can unintentionally set off in too many directions at once.
The answer will be different for individual industries and organizations, something we’ve seen through our work with hundreds of clients across the globe. One way to ensure an intentional approach is to stand up a team to govern your AI strategy and roadmap, something Avanade puts into practice through our Center for AI. This is home to cross-functional teams and initiatives that embed AI custodianship into everything we do—including how we innovate with AI and use it to transform ourselves.
With clear governance and a value framework, you can objectively assess and measure opportunities—from early experimentation through to scale. And remember, a centralized function is not about onerous processes which impede progress, and more about a flexible framework which lets you fail, learn quickly and move on.
#4 – Generative AI brings possibility and responsibility
Any organization using AI—and generative AI in particular—needs to accept that increased scaling means increased risk. 49% of senior leaders admit they’re not confident that their risk management processes are adequate for the integration of AI across their organizations.
To be useful and trusted by humans, AI must be built on a foundation that is secure, dependable and non-biased. In our early experience with Microsoft Copilot, we were encouraged to see that over 80% of our people judged it as fair and respectful of our corporate values. But there is still debate as to how humans will “behave” with AI, and we must keep responsibility, trust and transparency non-negotiable.
A Responsible AI Framework—that considers bias and discrimination, information security and data privacy, sustainability, and social implications—puts in place guardrails to help you understand the impact of AI across every corner of your organization.
#5 – Avoid unintended AI divides
Generative AI is often described as democratized and open for all—suggesting parity of access across all types of employees. But in reality, it’s highly likely that not everyone in your organization will get the same tool, at the same time. This requires considered decisions about when and which team, individual or process is onboarded.
To make adoption decisions fairly, we recommend that organizations apply a diversity and inclusion lens. This avoids the risk of unwanted ‘AI divides’ and instead lets you close digital skills gaps to empower employees with specific needs. As one example, our own experience uncovered Microsoft Copilot’s potential to better embrace neurodiversity.
We’d also recommend being mindful of perceptions across different parts of your organization— so you can proactively face into these as part of your change management efforts. Even the most senior leaders lack consensus when it comes to getting their people, processes and platforms ready for AI:
· While 69% of CTOs are very confident in their organization’s ability to harness AI faster than competitors, only 34% of CEOs have that same level of confidence.
· Although 58% of senior executives are highly confident in their understanding of generative AI and its governance needs, only 39% of mid-level management share the same sentiment.
When you think people-first and see AI adoption as a business transformation initiative, you will better navigate the inevitable learning curve that your organization will go through. This is a much bigger cultural and strategic shift than simply speeding up the things you’ve always done.
AI is coming—ready or not
As work becomes a collaborative effort between people and AI, we face an incredible opportunity. Success or failure depends less on technology and more on getting the critical organizational steps right. The challenge for leaders is to ensure AI is adopted in a responsible way, with a clear vision for how to reinvent work and ready employees.
