Market hype and growing
interest in artificial intelligence (AI) are
pushing established software vendors to introduce AI into their product
strategy, creating considerable confusion in the process, according to Gartner,
Inc. Analysts predict that by 2020, AI technologies will be virtually pervasive
in almost every new software product and service.
In January 2016, the term artificial
intelligence was not in the top 100 search terms on gartner.com. By May 2017, the term ranked at No. 7, indicating the
popularity of the topic and interest from Gartner clients in understanding how
AI can and should be used as part of their digital
business strategy. Gartner predicts
that by 2020, AI will be a top five investment priority for more than 30
percent of CIOs.
"As AI accelerates up the Hype Cycle, many software providers are looking to stake their
claim in the biggest gold rush in recent years," said Jim Hare, research vice president at Gartner. "AI offers
exciting possibilities, but unfortunately, most vendors are focused on the goal
of simply building and marketing an AI-based product rather than first
identifying needs, potential uses and the business value to customers."
AI refers to systems that change behaviors without being
explicitly programmed, based on data collected, usage analysis and other
observations. While there is a widely held fear that AI will replace humans,
the reality is that today's AI and machine
learning technologies can and do
greatly augment human capabilities. Machines can actually do some things better
and faster than humans, once trained; the combination of machines and humans
can accomplish more together than separately.
To successfully exploit the AI opportunity, technology
providers need to understand how to respond to three key issues:
1) Lack
of differentiation is creating confusion and delaying purchase decisions
The huge increase in startups and established vendors all
claiming to offer AI products without any real differentiation is confusing
buyers. More than 1,000 vendors with applications and platforms describe
themselves as AI vendors, or say they employ AI in their products.
Similar to greenwashing, in which companies exaggerate the
environmental-friendliness of their products or practices for business benefit,
many technology vendors are now "AI washing" by applying the AI label
a little too indiscriminately, according to Gartner. This widespread use of
"AI washing" is already having real consequences for investment in
the technology.
To build trust with end-user organizations vendors should
focus on building a collection of case studies with quantifiable results
achieved using AI.
"Use the term 'AI' wisely in your sales and marketing
materials," Hare said. "Be clear what differentiates your AI
offering and what problem it solves."
2) Proven,
less complex machine-learning capabilities can address many end-user needs
Advancements in AI, such as deep learning, are getting a lot of
buzz but are obfuscating the value of more straightforward, proven approaches.
Gartner recommends that vendors use the simplest approach that can do the job
over cutting-edge AI techniques.
3) Organizations
lack the skills to evaluate, build and deploy AI solutions
More than half the respondents to Gartner's 2017 AI development
strategies survey* indicated that the lack of necessary staff skills was the
top challenge to adopting AI in their organization.
The survey found organizations are currently seeking AI
solutions that can improve decision making and process automation. If they had
a choice, most organizations would prefer to buy embedded or packaged AI
solutions rather than trying to build a custom solution.
"Software vendors need to focus on offering solutions to
business problems rather than just cutting-edge technology," said Mr.
Hare. "Highlight how your AI solution helps address the skills shortage
and how it can deliver value faster than trying to build a custom AI solution
in-house."
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