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A new survey finds that most companies expect a high return on investment with their AI initiatives. However, many are still developing their AI business case and are stuck at the proof of concept stage.
Recently, we completed research to understand organizations’ experiences in developing and implementing AI solutions and emerging technologies, and the findings are eye opening. In fact, a particular tension in the U.S. stood out to me: 57% of U.S. business and government agency leaders surveyed expect up to 4x return on investment on AI copilots and agents, with most expecting a return in under 12 months. Yet, more than half are still developing their AI business case, and 41% are stuck at proof of concept. They’re impatient for ROI and stuck at proof of concept (PoC).
It makes me wonder how many have a visionary artificial intelligence strategy to which all ideas can be mapped (or, in the cases of not cleanly mapped, then scrapped). In my discussions with our clients about AI across all industries, I’m regularly asked, “Where do we start?” My answer: without a visionary strategy, AI initiatives are doomed to fail. Our study indicates that only 30% of organizations are developing one, suggesting a need to cut through the hype around short-term gratification; while the attraction of cost savings is tempting, this narrow focus distracts from AI’s transformative potential. Along those lines, we’re seeing that 75% of organizations are implementing AI out of the box or isolated to specific functions. That points to a potentially haphazard approach that scatters AI in various areas…again, without a cohesive strategy.
Developing a cohesive strategy starts with knowing your “why.” This north star will guide the innovation of new products and services with artificial intelligence, and it will be instrumental in unlocking more value from existing investments in cloud, data, and security. If you’re wondering how to prioritize the many steps to ready your people, processes, and platforms for artificial intelligence, here are a few questions to get the discussion going:
- Has your organization’s business strategy been updated to account for predicted generative AI growth and impact?
- Are you confident that the people-focused processes and roles that will be impacted by generative AI are clearly understood in your organization?
- How confident are you that leaders in your organization understand and are inspired by generative AI and its governance needs?
- How much support do you think will be required to onboard/train workers to make the most of and innovate with generative AI tools, such as Microsoft 365 Copilot?
- What kind of new divisions might generative AI create between enabled and unenabled employees?
See also: With AI Agents on the Scene, Structured Data is Back in Vogue
The good news is that the research shows positive movement in readiness efforts. U.S. organizations are putting in the necessary and hard work to gain long-term artificial intelligence value: 98% have accelerated legacy modernization plans; 97% are planning to accelerate cloud adoption; and 96% agree the ability to secure sensitive data will be the make or break for organizational reputation. Laying this groundwork is imperative if U.S. organizations want to achieve their number one priority: integrating AI into processes for new revenue streams. It’s ambitious, but it’s also the kind of bold thinking that AI demands.
Getting your platforms and data ready doesn’t mean you can’t still experiment. Start a small pilot to evaluate potential impact and understand if there’s a business case for scaling. An experienced partner will guide you on assessing and implementing the right data and technology tools to enable use cases. For those organizations struggling to launch proofs of concept because their employees aren’t ready to take that on, the right partner will also have the ability to execute and expand on your behalf.
Finally, a word about workforce readiness. AI is transforming workplaces, but successful adoption requires prioritizing people over technology. AI fluency is an imperative for the whole organization and must be fully woven into your AI strategy and roadmap to manage the socio-emotional aspects of this technology. Most U.S. organizations are in tune with this: 98% are prioritizing upskilling their workforce and creating new jobs to off-set potential AI job displacement; 84% are focusing on change management to ensure AI supports both new and existing ways of working; and 81% plan to increase investment for training and fluency to help employees adopt emerging tech tools.
No matter their degree of readiness, 81% of our survey respondents agree they’re at risk of losing their competitive edge by not implementing artificial intelligence quickly enough. If you can relate, you may want to learn more about the AI gaps and opportunities our research has uncovered and how you can find the right PoCs for business value.