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This content is part of the Essential Guide: How to build an AI services business in the channel
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How to grow your AI services business

Getting to the next stage of AI growth calls for IT service providers to consider security, marketing and ROI. A talent for demystifying technology also helps.

Making sure your IT service provider business receives a steady flow of new customers looking for AI services and solutions will take a platform strategy, innovation, IT skills and an ability to align AI projects to your customers' business priorities.

Once you've captured your first client and your business begins to brand itself as an AI solution provider, you'll have to grapple with an evolving AI market that requires a continuing investment in partner ecosystems, skills and intellectual property to gain traction and trust among customers.

A PwC survey of 1,000 executives suggested determining how to build a trustworthy AI solution raises a number of key customer concerns. Survey participants said they needed to keep in mind how to build AI algorithms that reduce bias in the data and create AI models that can make accurate decisions.

The ability to build confidence in AI models that customers can rely on for performance and security is another key challenge. Survey respondents also pointed to the need for a clearer understanding of what governance will be applied to AI systems and the data they manage and whether these systems will be in compliance with regulations.

Additionally, executives want to know what impact AI systems will have on their customers and employees.

Editor's note: This is the second of two stories that examine what it takes to succeed in the AI services business. The first article explored how to launch an AI solutions operation. This feature discusses how to grow a business once the initial customers are on board.

Emphasize security to grow AI services

Reflecting on their own journey, executives at KenSci, a Seattle-based company that uses its healthcare machine learning platform to help predict care outcomes and cost, said security vulnerabilities were at the top of their concerns when they approached healthcare organizations with AI solutions.

When considering the Health Insurance Portability and Accountability Act (HIPAA) of 1996, for example, KenSci's executives decided to deploy machine learning algorithms within their customers' IT infrastructure to better protect them from a third-party patient data breach. HIPAA governs the way healthcare organizations protect individuals' medical records and other personal health information.

Sunny NeogiSunny Neogi

"Typically, in the [SaaS] business, customers send their data onto an off-premises platform, and that platform keeps the data and tells customers what to do. We realized healthcare data requires a different approach," said Sunny Neogi, KenSci's chief growth officer. "To reduce vulnerabilities, we decided to put our platform inside our customer's data center. We don't bring any data out of our customers' infrastructure; we bring our platform to their infrastructure so that the platform sits inside wherever their data sits."

To enhance its ability to manage protected health information, KenSci partners with large healthcare organizations that have the resources in place to provide patient data security and data governance programs.

"Our strategy is essentially to go and work with the large customers, like the Centers for Disease Control and Prevention or England's National Health Service. They're big enough, and the data is good enough, and if they succeed with their AI projects, the smaller customers will learn from them and start doing what they are doing today," Neogi said. "The healthcare market, in its entirety, is not ready for AI, but many of the big customers are doing some incredible work with machine learning."

Keep an eye on the big picture

Companies building out their AI services practice should also embrace the way the technology is changing the IT world around them. According to the Gartner 2019 CIO Survey, the number of enterprises deploying AI grew 270% in the past four years and has tripled in the past year.

Ken SeierKen Seier

One way to start looking at how to add customers is to understand the "big picture," said Ken Seier, chief architect for data and AI at Insight Enterprises Inc., a company based in Tempe, Ariz., that provides B2B and IT solutions for large customers.

Seier said IT service providers need to envision AI as the new tool that will deliver value to their client's business in the form of customer engagement, workforce empowerment and business optimization. To do this, AI needs to be associated with technological advancements, such as developments in the cloud platforms, mobile applications, dashboard reporting, IoT and connected devices.

"Just saying that we are going to be developing AI is really just one piece of a very large puzzle that goes all the way from DevOps and development practices to customer engagement and user experience, and it has to be synthesized into that full picture in order to succeed," Seier said.

AI in business: focus on tangible benefits for growth

Dana BergDana Berg

Companies providing AI solutions also need to keep in mind that customers and the IT market in general are still looking for clarity about how an AI project will benefit them and what an AI deployment will mean for their business, said Dana Berg, COO at SADA Systems, a North Hollywood, Calif., business consulting and technology service firm.

"You are not selling, generally, a [SaaS] product," Berg said. "You are not selling, per se, something that is so generic that it's applicable to every single customer, because artificial intelligence for one customer is very different to another based upon the business that they are in and the problems that they need to solve."

AI providers need to demystify artificial intelligence and be very clear as to how that is going to be something that could be intriguing to that particular customer.
Dana BergCOO, SADA Systems

The design of a machine learning algorithm is different for each use case in each vertical market, Berg said. As a result, the AI marketing message and sales pitch have to be relevant to each sector, such as healthcare, financial services or retail, he added.

Furthermore, IT service providers can't simply offer a blanket story or value proposition that will always resonate with a wide variety of companies. Indeed, AI providers will have to develop marketing methods that are specific to the customers they are communicating with.

"AI providers need to demystify artificial intelligence and be very clear as to how that is going to be something that could be intriguing to that particular customer," Berg said. "On the sales side, if, in fact, you do get interest and customers are intrigued by virtue of a message that you just marketed, it needs to be supported in the sales cycle with someone at the IT provider firm who is equally as specific -- someone who can credibly show they understand how AI can impact the customer."

Rethink marketing to boost AI services

Carolyn AprilCarolyn April

When selling AI, IT service providers should also bear in mind that they are not marketing or selling a product, but instead are selling their ability to build AI algorithms and offer analytics around that, said Carolyn April, senior director of industry analysis at CompTIA Inc.

"AI is not exactly transactional, so it is not the same as an IT services provider saying, 'Hey, your whole department needs some new desktops; we are going to come and sell those to you.' That's a very different type of marketing approach than something that's a little bit more esoteric like AI," April said. "Channel companies are not really selling AI; they are selling the capabilities or the outcomes of AI. Because of that, the sales and marketing approach changes in that their messaging is much more business consulting than it is technology-focused."

To make progress, IT companies will have to look at a variety of ways to keep upskilling and reskilling their AI teams. Companies must look for a variety of partners, such as distributors and associations, as well as community colleges and universities, to tap individuals with skills that are in high demand, April noted.

Companies may also want to retrain their existing employees if they think their workers can make the leap from whatever they are doing now to becoming more skilled at AI and data analytics.

"It's multifaceted, how you approach it," April explained. "You can retrain internally and lean on those vendor partners who can help you, and you can look externally for younger people coming into the workforce and try to hire from the outside as well."

Build on the cloud platform

Like so many new technology implementations, customers want to know how AI can help across all aspects of their business. They want to know if AI solutions will improve workflow, create efficiency, save money and help them compete. They also need a better understanding of how AI projects build on their previous investments in IT.

"In our conversations with customers, AI dovetails directly into their larger cloud return on investment strategy," SADA Systems' Berg said. "By using cloud platforms to build machine learning models, which harvest a company's information and data, AI creates more responsiveness, helps companies be more proactive, generates better customer experiences and, depending upon the use case, allows companies to experience better efficiency and lower cost."

Building an AI practice can also help IT service providers appeal to an increasing number of customers, while differentiating them from their competitors, Berg said. Channel companies, he said, have an opportunity to create their own intellectual property when they stitch together the baseline infrastructure the cloud provides with an AI-capable product a vendor provides.

"The more that they are able to differentiate themselves that way, the more money they are going to be able to make," Berg said.

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