As the amount of data grows exponentially and computing power strengthens, now is the time for business applications to get a boost from artificial intelligence.
Artificial intelligence seems to be everywhere. Google knows what you're thinking when you start typing in its search bar. Amazon knows what you want to buy next with its recommendation engine. And there's an abundance of creatively named virtual assistants to tell us what we want to know -- from Alexa to Siri to Cortana. All of these insights into what we think, want and want to know have one thing in common: They're all highly sought after by companies in the business of marketing, selling and providing customer service to us.
AI applications have caught on in some consumer-facing industries and specific procedural services like programmatic media buying and financial services. And we've all been victims of some of the earliest forms of AI with the "press zero for operator" contact center voice assistant. The majority of sales, marketing and customer service companies, however, are just dipping their toes into the ocean of AI applications, tools and services.
"Businesses need to understand how people make decisions. They know how people act, but they don't really know how people think and decide," said John Marshall, chief strategy and innovation officer of consultancy Lippincott. "Over time, the diversity of information and the trail we lead will start to get integrated into AI and into better decision-making algorithms. Some of the technical problems right now will be solved."
Grabbing big data by the tail
With the increase in natural language processing, previously unforeseen amounts of data and the technology available to handle it all, the groundwork has been laid for a potentially massive migration to AI applications in business. With this migration comes the promise of smarter and timelier insight, better efficiency and time saved, and algorithms that constantly improve for as long as the data keeps churning.
More than 40% of technology pros surveyed by TechTarget Inc. said their company plans to implement big data and business analytics initiatives in 2017, while 38% favored IT automation and nearly 20% the internet of things (IoT). In comparison, less than 38% of respondents to the 2016 survey cited big data and business analytics as an initiative they planned to implement, and less than 16% favored IoT implementation. IT automation received no responses.
[An AI app doesn't] come out of the box knowing what to do. It's like a little baby. It needs to learn.
Joe Stanhopeprincipal analyst, Forrester Research
To reap the benefits of these applications, platforms and services, a business needs to do certain things -- such as have enough data, patience and a culture willing to adapt to change -- or else AI will be the latest sunk cost. "Marketers and organizations need to have the discipline to carefully train these environments," said Joe Stanhope, principal analyst at Forrester Research. "They don't come out of the box knowing what to do. It's like a little baby. It needs to learn."
Looking for needles in haystacks
John Marshall
The optimism around AI applications for business services is justified. AI works by mining extensive sets of data for patterns or logic too minute or time-consuming for humans. Ninety percent of the world's data was created in the past two years, according to IBM, and those gigabytes are expected to increase exponentially in the coming years. Combined with computing capabilities strengthening every year, AI insight for businesses is finally becoming a reality that will evolve over the next several years.
The first generation of AI app was "an efficiency play," Stanhope said, and it has hit the business applications market in the form of chatbots, virtual assistants, and automation of mundane and repetitive processes. "The second generation," he predicted, "is when it becomes good enough to service insights and find needles in haystacks that we as humans couldn't find. The real promise, however, is having a system that can continuously optimize the marketing and customer experience. It doesn't just service insight and crunch data; it can go ahead and make changes as well."
'Intelligent security' AI's linchpin for business apps
Michael Fauscette
A promising application for artificial intelligence in business is security. Protecting a company's data and information and complying with regulatory requirements demands a significant investment. According to Gartner, IT security spending grew nearly 8% in 2016 to $81.6 billion; half of businesses currently implement some form of data loss prevention, and by next year, nine in 10 businesses will have IT security in place.
"There are a couple new activities driving the use of AI, one being intelligent things and the other being intelligent security," said Michael Fauscette, chief research officer for G2 Crowd, a peer-to-peer business software review company. "Soon, you'll be able to embed AI into security and predict when there are threats or react to the first indication of an attack before you could have with human intervention."
While security is a frontier that AI applications are just beginning to navigate, analysts warn technology vendors and organizations that are in a position to reap the benefits of those tools to get in on the ground floor or risk being left out in the cold.
"Look at the whole movement around social tools [a decade ago] and the idea that ... people will communicate with nonembedded tools," Fauscette said. "Ten years into it, the ones being used are the ones embedded in their applications. AI will catch on because it's there and the benefits can quickly be seen. Most companies involved in enterprise apps will have to do something to answer to that."
Software application vendors are currently releasing tools that promise AI insights by using predictive analytics and combing through data to suggest best practices and next steps for marketing and sales reps and proactively solve problems for service reps. "We looked at the market, saw the ecosystem of AI-powered consumer apps emerging with Siri and shopping on Amazon and how [user interfaces] are more personalized," said Jim Sinai, vice president of marketing for Salesforce Einstein. "All of that paved the way for us to say the technology is ready now, and that kick-started the huge internal effort at Salesforce to double down in AI investment."
Jim Sinai
"Double down" may be an understatement, as Salesforce went on an acquisition spree in 2016, spending more than $5 billion to buy 10 companies, most of them AI-based. Those acquisitions and integrations soon led to the release of Einstein, Salesforce's AI-powered engine for its entire business applications platform. Salesforce is currently rolling out its Einstein upgrade cloud by cloud, with Service Cloud as the latest. "Customers want a system that will learn across their data and entire CRM system," Sinai said.
Early stages of applications for AI can be found in the major platform players, including Salesforce, Microsoft and Oracle, as well as a growing market of third-party tools that can provide specific capabilities around automation and insight and allow reps to focus on specific leads or to work on more complicated and valuable accounts. But that next frontier of almost knowing what a customer wants before he or she does is still on the horizon.
John Marshall
Michael Fauscette
Jim Sinai
