Special Report: Artificial intelligence apps come of age
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SugarCRM Inc. co-founder Clint Oram recalled discussing the potential of CRM systems to predict sales with machine learning more than 15 years ago.
"Sitting around as a product manager, kicking around the ideas that are coming out today, the limiting factor back then was technology was really hard to deploy and extremely expensive," Oram said. "What's changed? Software as a service, mobile and social all became prominent."
Back then, CRM systems were mostly on premises and operated as Excel replacements and static data-entry systems. Then, cloud-based CRM entered the scene and opened the door to modern tools underpinned by machine learning and artificial intelligence technologies.
Now, as industry leaders like Salesforce acquire data intelligence companies, there's a move toward creating cloud-based CRM systems that act as digital assistants, rather than data input tools.
"Gone are the days where CRM is just a database," said Jon Lee, co-founder and CEO of ProsperWorks Inc., based in San Francisco. "There has to be some inherent value. Managers know what the general practices in sales should be through decades of doing it, and tuning your algorithms around those best practices gets you 80% there. I think the big opportunity to optimize is using the data available to us to notice things we haven't noticed before to get us the other 20%."
AI technologies driven by data
Artificial intelligence (AI) is booming. According to research by Gartner, 20% of business content will be created by machines by 2018, and 6 billion connected devices will require the ability to connect and share data with other devices.
Jon Leeco-founder and CEO, ProsperWorks
CRM professionals point to two primary developments that fuel the increase of artificial intelligence technologies. First, there's the increase in vast amounts of data that needs sorting and understanding. Then, there's the move to cloud CRM systems, which enables the intake and dissection of data from dozens of digital sources.
"You can't draw machine-based learning conclusions off small data sets," Oram said. "We're at the front end of massive data sets and big data driving the next evolution of CRMs. You can see the need for AI coming on the heels of that."
There are dozens of sources online from which CRM companies can draw information, including social sites like Facebook and Twitter. They can also utilize public records, including police reports, court records or property-ownership records.
With all the information across devices and platforms available, it does a company little good if it doesn't have a way to integrate the data into its CRM. That's where the advancement in cloud CRM tools helped set the stage for the need for AI.
"In the past, it was on-premises software, and there was more friction and larger wall between data and third-party apps," Lee said. "The access to data increased dramatically, and, in the past, that required a lot of integration. The world moved to the cloud, and now you have the opportunity to analyze not just your company's data, but data from other companies and different categories. You start finding patterns."
Security concerns in the cloud
The conversion for companies to cloud-based systems is ongoing. According to Gartner, the software-as-a-service industry has grown more than 20% from 2015 to 2016, ballooning into a $37.7 billion industry.
The growth is spurred by customers' increased comfort in the security of cloud-based services, according to David Schmaier, CEO and founder of Vlocity Inc., based in San Francisco. Schmaier has worked with CRM systems for nearly 30 years.
"There was a big fear of data security on the cloud," Schmaier said. "People weren't sure if you could scale these cloud systems for hundreds of thousands of users. We proved we can."
That's not to say issues with security will be nonexistent in the cloud, but Gartner predicted the majority of security failures -- 95% -- will be the customer's fault, not the service provider's.
By building up cloud-based services and demonstrating they worked, the industry laid the groundwork for heavy investment in artificial intelligence technologies.
"Cloud technology needed to provide all the capabilities that on-premises systems provided. It takes a while to build out that capability," Schmaier said. "The plumbing and infrastructure are making [artificial intelligence technologies] work."
While the technology was built out to support artificial intelligence technologies and cloud-based services in the 2000s and 2010s, it also took a sociological migration to adopt these services.
"Customer-facing professionals in 1999 and 2000, they hated using tech," Oram said. "Now, we have a workforce that has grown with technology at their fingertips."
With the changes in the market in full effect, companies that invested in on-premises, legacy software are playing catch-up.
"The only reason companies still have on-premises is the legacy of thousands of dollars spent and decisions made," Schmaier said. "It's a technical debt that needs to be paid."
'Everyone sees it as the future'
AI technologies are becoming more important to the world of business applications each year. And with more integration, data sets and machine learning capabilities, the technology should continuously get more advanced, which could be concerning for sales reps whose job it is to make decisions that now are left to software.
Industry professionals say the concern of artificial intelligence technologies taking over entry- or midlevel positions is overblown. Some form of human interaction, whether with the customer or with the software, will be necessary.
"AI is only as good as the way you train it, and it requires a human to train it to get smarter and smarter," Lee said. "AI needs all that data, but it also needs a seamless front-end and human experience to actively train it."
Oram dubbed the current period the age of data, and said there's no turning back from the mass amounts of information consumers have voluntarily and involuntarily made public.
"Between the massive data explosion, coupled with internet of things, we're in that era right now in a big way," Oram said. "There's an amazing wealth of personal data we're consciously and unconsciously publishing. We're squarely in the age of data, and [artificial intelligence technologies] are coming right along."
With AI comes the need for machine learning, or the capability for artificial intelligence technologies to learn the best practices from the information it has captured.
"There's an AI and machine learning bubble going on," Lee said. "Everyone sees it as the future. You'll see machine learning applied across a number of industries -- CRM being one, [human resources] being another. It will transform how we work. The use cases are ongoing for what specifically can we apply this capability."
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