Help Clients Find Value in AI

How vendors’ product and general managers can differentiate, add value and avoid adding more confusion in a noisy AI market.

In 2016, the number of inquiries with Gartner clients who used the term “artificial intelligence” (AI) increased more than 500%. The first five months of 2017 saw more client inquiries about AI than in all of 2016, and the trend continues. Hype around AI has reached critical mass, and end users are clamoring for clarity.

Meanwhile, technology service providers (TSPs) market and promote AI as a magic elixir that will solve every business problem with automation. The hyperincrease in startups and established vendors all claiming to offer AI products without any real differentiation is creating confusion at end-user organizations and delaying purchase decisions.

This confusion presents an opportunity for vendors to communicate clearly and solve real business problems for clients. “There is a big opportunity for TSPs to educate clients about how AI can help them in a business context,” says Jim Hare, Gartner research VP.

This means there is a short window of opportunity to use AI in sales and marketing materials

There is no time to waste reorienting messaging toward an approach anchored in strategic business solutions: Gartner predicts that by 2020, AI technologies will be virtually pervasive in almost every new software product and service and by 2021, the term AI will no longer be considered a differentiator in marketing tech provider solutions. This means there is a short window of opportunity to use AI in sales and marketing materials.

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Link solutions to client business value

Hare advises vendors to educate and not obfuscate. Clients need guidance on how a specific AI solution will solve their specific challenge and address mission critical priorities. Most organizations believe AI is solely about automation and may not fully grasp how a particular solution can do more than just automate. “Buyers don’t want AI technologies,” says Hare. “They want solutions to problems.”  

TSPs will likely build more credibility and have better reception with buyers by positioning AI as “augmented intelligence” rather than “artificial intelligence”.  Augmented intelligence will augment organizations’ employees, customers and ecosystem participants to do more with humans and machines together than either could do separately.

Focus on client “big plays”

TSPs have an opportunity to educate and align their solution around critical client strategic initiatives — their “big plays.” Improving customer experience is the biggest initial reason for adopting AI, according to the Gartner 2018 AI Business Value Forecast, but it’s not the only business goal that organizations are pursuing. Gartner Research Circle discussions indicate a desire to improve speed and efficiency as well as achieve better data processing and analytics.

Members of the Research Circle mentioned the ability to utilize staff more efficiently on value-add processes and leverage the treasure trove of unstructured data for analysis and future efficiencies as key business goals of adopting AI. “Have messages that resonate with the client’s challenges and ensure your solution aligns to their big play,” says Hare.

Get your (AI) FAQs straight

AI buyers have key questions that TSPs need to be ready to answer in the sales cycle including:

  1. How is your product superior to current options that have no AI?
  2. How does AI in your product improve business performance?
  3. How does your product work using the prospect’s or client’s data?
  4. What data and compute requirements do clients need to use your product?
  5. How much time and resources are needed to support your product?

Next steps

Focus on how AI solves problems, rather than offering just another technology. Be prepared to (clearly) explain how your solution helps organizations overcome barriers to adopting AI. Use the term AI wisely in your sales and marketing materials and be clear what differentiates your AI offering along with what problem it solves.

Regardless of entry point, technologies need to be deployed to specific and measurable outcomes for a particular use case. “Focus your AI go-to-market on how it gives customers an unfair advantage,” says Hare.

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