If AI is so transformative, why haven’t more enterprises embraced it already? Perhaps we’ve been trying to force a square peg into a round hole by asking people to adapt to AI, instead of the other way around.
At Microsoft, we’re striving to change that. We believe business users closest to specific problems have the greatest insights in how to solve them. And so we’re putting AI into their hands.
In our Reimagining AI for Microsoft Business Applications blog series, we offer suggestions to help you capitalize on the enormous promise of AI. We start by exploring difficulties that often occur when trying to drive better outcomes through AI. And we offer our perspective on how to transcend these challenges and propel your business forward.
Industry reality: Enterprises are rushing to adopt AI, but ROI is lagging.
Expectations for AI are sky-high among business executives. A global study by The Economist Intelligence Unit reports that 90 percent of the participating leaders anticipate that AI will have a positive impact on their growth, and 85 percent on their productivity.
And yet there’s a gap between expectations and reality, as noted in a recent McKinsey survey of over 2,000 organizations. Nearly half of these respondents report embedding AI in at least one of their standard business processes, and yet only 21 percent have rolled it out in multiple areas.
The problem may be an approach to AI that focuses on technology more than on business outcomes, and on effective implementation more than an effective workforce. As a result, either the returns aren’t there or the solutions can’t scale.
If we approach AI as a technology to be implemented, these 3 roadblocks often emerge.
Outsourcing AI provides immediate gains but limits ROI and long-term viability.
Outsourcing enables you to add functionality without taxing your existing infrastructure or staff. This can be a great option if all you’re seeking is a single point solution.
But if your intention is to extend AI capabilities, you need to cultivate in-house expertise and plan for scalability to recoup the full value of your investment. And you need to consider whether outsourcing is cost-prohibitive over time.
A skills gap in data science can create IT bottlenecks and prolong development timelines.
Because the technology is so new, there’s a significant shortage of data science professionals with AI experience. So if you opt to develop AI solutions in-house, implementation may have to wait until you hire people with the right expertise.
And if your approach is to centralize AI development, you will be tasking your data scientists with mastering line of business processes and workflows. Needing to gain skills and knowledge in areas like customer insights, product insights, and fraud detection can significantly slow down schedules.
Business users may have difficulty adopting AI due to overwhelm or fear.
In-house AI technologies that don’t centralize IT face the opposite problem; they require business users to develop AI expertise. This creates a dilemma for business leaders and professionals. How will building an AI skillset enhance their ability to excel? It will certainly drain their efficiency, distracting them from their goals and limiting their ability to innovate. It also can make them fearful of being replaced and leave them feeling undervalued.
Avoid these roadblocks with AI focused on amplifying human capabilities.
Look for AI that adapts to your business strategy and your workforce needs.
Fundamentally, Microsoft believes that AI technology should empower you and your employees to achieve more. To facilitate that, our AI is a core ingredient in Microsoft Business Applications, infused across our offerings.
This lets you insource your AI transformation in whatever way suits you. There’s no need to adopt a new system. Your data, applications, and tools are already unified on a single platform that’s scalable, secure, and flexible, speeding ROI.
Empower your data scientists to focus on innovation and new development.
We meet your organization wherever you are to create a clear path to transformation using AI. Our tools are woven into line of business workflows, making them more self-serve for business users. So while you still need to hire top-level data scientists, they’re free to focus on more critical needs. And while performance benchmarks are important, we think beyond them, helping you implement solutions with the least disruption and most usability.
Empower business users to work with AI on their own terms.
Our mission is to bring AI to problem solvers and to support your business users in developing their own AI solutions even as they strengthen their core competencies. They have direct access to AI tools in their workflows, so they can leverage their own knowledge and expertise to think bigger, and be more effective.
When you use an AI solution that makes people, not technology, the hero – you unify relationships, processes, and data across applications, so business leaders and users have increased visibility and control to do their best work.
Next time in Reimagining AI for Microsoft Business Applications, we will look at specific ways that building AI solutions around domain expertise can drive success throughout your organization.