7 Ways to Sell Artificial Intelligence to Businesses More Effectively

7 Ways to Sell Artificial Intelligence to Businesses More Effectively

Assume you've been chosen as a proponent for incorporating artificial intelligence into your company. Are you going to discuss algorithms, training data, test data, supervised learning, unsupervised learning, and deep learning neural networks with executives? Keep an eye on how their pupils dilate.

It's not that executives aren't getting the AI message. According to a recent IBM study, the global AI adoption rate has steadily increased to 35%, a four-point increase from the previous year. The study shows that using AI to automate IT, business, or network processes has real benefits, such as saving money and time (54%), improving IT or network performance (53%), and giving customers a better experience (48%).

However, incorporating AI requires changes to the organization as well as the systems and processes that have defined the way business is done. To sell AI in a new way, you need to have some empathy, dexterity, and business sense.

The following are suggestions made by industry experts who work every day to promote greater AI adoption:

Before introducing technology, consider and comprehend the problem at hand. Rather than coming in and asking for a blank check to tackle numerous ambiguous goals, identify a single problem and outline a clear strategy for how AI will solve it, says Sagar Shah, client partner at Fractal Analytics. "Highlight quick wins that can be accomplished in the first 12 weeks of the project." This gives skeptics clear parameters to compare and judge results against. "

It's a matter of spending more time determining which problems require AI to be applied to them. "The single most significant impediment to AI success is relying on unscientific assumptions and broad goals, rather than taking the time to frame the exact problems they are attempting to solve," Shah says. "To put it simply, the more time a company spends ahead of time on a problem, the better AI product adoption will be." 

Set reasonable expectations. "Be realistic about what AI can do," says Alex Saric, smart procurement expert and CMO at Ivalua. "It can be a useful tool, but algorithms have a long way to go." It is critical to set realistic short-term goals and work to improve over time. Leaders must sell AI in a way that explains how it will help employees focus and become more engaged and productive, rather than displace them. " People frequently mistake artificial intelligence for innovation rather than "really understanding what it means for them and how it will be applied every day," Shah agrees. "Sometimes, a more traditional approach may work better than one that uses AI, so buyers need to pay close attention to the details."

Bring in talent, but don't try to build everything yourself. While AI is viewed as a labor saver, another recent IBM study finds that the skills gap remains the most significant barrier to AI adoption. "The talent gap is significant," says Flavio Villanustre, senior vice president and global chief information security officer at LexisNexis Risk Solutions. "It is usually not cost-effective for a company to develop its own algorithms, unless selling services or products based on those algorithms is part of the company's core business strategy." Too many businesses "invest in forming an internal team to build AI solutions end-to-end," says Sivakumar Lakshmanan, co-CEO of antuit.ai, which is now part of Zebra Technologies.

Consider the long term. Another common misconception is that businesses must implement AI all at once and that every project must be an immediate success, or else their investment will be squandered, Shah says. "Adopting AI is a big step for any organization, so start by applying AI to a handful of strategic problems—of which only a few will work as expected right away—and then apply the lessons you've learned to another set of projects, and then another." Businesses must also remember that AI is not a single tool. Instead, it is the result of ongoing engineering, design, and behavioral science research. All of these elements must work together. "

Rethink your processes. AI cannot simply be layered on top of existing processes and expect to be successful. According to Lakshmanan, a common mistake is "fitting AI on top of an existing process that is centered on manual, committee-based decision making." "In this case, AI is merely a checkbox item. Rather, adapt the processes to the newer world; for example, you do not buy an e-book on a device to print out and read. "

To ensure data transparency and trust. "The technology itself must make how AI output is generated more transparent," says Saric. "Remember that for many years, AI has been used to help classify invoice lines from company purchases in order to accurately determine where the budget is spent." However, many approaches are black boxes, and when users discover errors among millions of lines classified, they lose trust and stop relying on the data. "The quality of AI output is highly dependent on data quality and volume," he adds, "but substantial amounts of organizational data are still dispersed across many systems and of questionable quality." To reap the benefits of AI, organizations must gain control of enterprise-wide data. " Building a solid data foundation, as well as leveraging master data management solutions and platforms with unified data for specific functions—suppliers, customers—can address this, but are not widely implemented today."

Employees at all levels should be involved. "Businesses fall into the trap once they recognize the problem of rushing a tool into production without significant collaboration and end-user input," Shah says. "In order to drive AI tool adoption, businesses must co-create them with end-users so that they not only solve a problem in theory, but also in practice." Even with strong co-creation and problem framing, long-term adoption is dependent on businesses and their AI partners constantly working on improvements. New requirements and wrinkles emerge all the time. And the only way to ensure your company's long-term success is to accept that AI is a living, breathing tool that requires constant tweaking rather than a one-time plug-and-play solution.