Enterprise AI

How to win with AI

MIT Sloan recently published a research report on artificial intelligence in partnership with Boston Consulting Group. Compiling the findings of a survey of more than 2,500 executives, the report found that while 90 percent of business leaders acknowledge that AI is a business opportunity for their company, the vast majority (70 percent) are struggling to deliver value with it.

While there are many reasons why companies struggle to create value with AI, among some of the most common noted in the report include:

  • Failing to actively align business owners, process owners, and AI owners

  • Relegating AI to the IT team, rather than seeing it as part of a broader digital transformation initiative

  • Not building a strong internal team that consists of both imported talent for select technical leadership roles as well as an upskilled, AI-literate workforce

Other challenges include not having access to the quantity and quality of data necessary to power AI, lacking the internal resources to scale AI capabilities, and the so-called black box problem that occurs when companies can’t explain how AI does what it does.

Although companies may struggle with any of these challenges, or others, the reality is that they don’t have to. In this post, we’ll explore some of the ways businesses can ensure that their AI projects are a resounding success.

Unlocking AI’s value

While setting your business up for AI success is certainly no small feat, there are some best practices that you can follow that will get you there faster:

  • Define your purpose. What exactly is it that you’re hoping to achieve by adopting AI? Do you want to build better products or go to market faster? Are there other areas of the business that could benefit from AI beyond your product? Do you see it as a risk mitigation play? Knowing precisely what it is that you want to achieve will help bring some discipline and focus to the strategy you create.

  • Track everything. Take care to meticulously track your projects. The goal isn’t to inhibit experimentation, but rather to give you a baseline from which you can adjust your strategy on an ongoing basis. The more you can study and learn from what you’ve done, the faster you’ll find yourself on the right path.

  • Focus on education. Data science skills are essential to extracting value out of AI. Yet it can be challenging to find and recruit professionals with these skillsets. For that reason, upskilling your existing workforce is essential. Giving your employees access to additional training through online classes, for example, is a great way to help ensure that they’re ready to do the work you need them to.

  • Be realistic. Extracting long-term value from AI won’t happen overnight. You need to take a long-term view and be prepared to invest the time and resources necessary to get results. Make sure that everyone in your organization has a clear and accurate view of the value that AI can actually deliver and how long it will take to bring that to fruition.

  • Make a call about build versus buy. Most companies feel that they need to make a definitive decision about whether to build AI systems in-house or simply buy them. Yet when it comes to building versus buying, there aren’t any hard rules. In fact, the best solution is often to do a little bit of both. Taking a hybrid approach can help you scale your AI capabilities and ensure that you get results faster.

While the path to successfully integrating AI into your business isn’t necessarily easy, it’s certainly possible. By following the best practices outlined above and applying the right focus, discipline, and resources, your company will be able to extract considerable value from AI. For more valuable resources that can help, check out: Step up your conversion rate with AI.

Finally, if you’re more the talking type why don’t you get in touch with us, and one of our experts can fill you in on how we help businesses (and their customers) get the most out of AI.


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