Artificial intelligence (AI) is the not-so-secret weapon in the modern enterprise. Everyone — from software vendors to social networking sites, from analytics companies to retailers — are investing in machine learning.

AI is nothing new. As CMSWire contributor Tom Petrocelli recently explained, "real research into what we call AI, especially natural language processing (NLP), visual and audio pattern matching, machine learning and processing text for context and meaning, has been underway for over 40 years."

But trends like social media, big data and the Internet of Things have collectively fueled interest in AI, which "now has a serious purpose — driving complexity for the end user out of computer systems and data," Petrocelli noted.

By 2018, Gartner predicts machines will author 20 percent of all business content, and by the end of 2018, customer digital assistants will be able to recognize us by face and voice across different channels.

Automated composition engines can use natural language writing to produce white papers, press releases and legal documents. Machines have the ability to take massive amounts of information and data and learn from it fast — faster than humans.

Amazon has entered the game with Alexa, the voice assistant for Echo, and Google, Apple and Microsoft continue duking it out with Google Now, Siri and Cortana, respectively.

The Question

Why is AI the new power fuel in the enterprise?

The Answers

Amit Bendov, CEO,

Amit Bendov headshot

Bendov is CEO and co-founder of, a startup just coming out of stealth today. Headquartered in both Tel Aviv and Palo Alto, Calif., the year-old Software-as-a-Service (SaaS) platform announced $6 million in Series A funding led by Norwest Venture Partners and Check Point co-founder Shlomo Kramer. The company aims to "help sales people succeed, help companies to sell more, and help buyers enjoy a better experience." With more than 20 years of senior leadership experience in hyper-growth technology startups and publicly traded companies, Bendov has managed R&D, marketing and sales at global corporations in North America, Europe and APAC. Before, he was CEO at Sisense, Panaya and ClickSoftware. Tweet to Amit Bendov.

The first wave of SaaS applications is over. SaaS companies like Workday, Salesforce, NetSuite, Marketo and Zendesk have automated every square inch of business workflows. Finance, HR, sales, marketing, support, supply chain and others have all been automated.

These applications have two fundamental functions: to keep the records and automate workflows. For example, Marketo keeps track of my leads and can send them emails based on various triggers. Salesforce keeps my contacts and sales opportunities and can trigger invoice creation when a deal is won.

But after some 15 years of SaaS market development, almost all business processes now have solutions that address them. Workflow SaaS is now turning into a commodity market. And from a user perspective, having a CRM or marketing automation software is no longer a competitive advantage — just like hotels can’t use their plumbing to lure customers. It's a mere entry ticket.

The next tsunami of innovation is here, and it’s machine learning SaaS. AI and machine learning can finally tackle problems infinitely more complex than business workflow.

AI is the next unfair competitive advantage for users.

For example, marketing automation software can help with scheduling of email campaigns or with A/B testing. But how about an AI SaaS that can actually create killer copy for landing pages?

Similarly, your CRM can store your contacts’ phone numbers and may even dial them for you. But it cannot help with what to say once you have them on the phone. Sales conversations are nuanced, complex and difficult to master. The winning plays cannot be described by simple if/then workflow rules.

Laurence Lock Lee, Chief Scientist, Swoop Analytics

Laurence Lock Lee headshot

Lee is the co-founder and chief scientist at Sydney-based Swoop Analytics, a company that provides enterprise online social networking analytics dashboards. He has held senior positions in research, management and technology consulting at BHP Billiton, Computer Sciences Corporation and Optimice. He specializes in applying social and organizational network analysis techniques to business problems. Tweet to Laurence Lock Lee.

As we move into the world of the IoT and big data, the opportunity for using more sophisticated AI-inspired search will enable us to continue to offload the more tedious, nearly mechanical searches that computers can do so much more efficiently than humans.

While many of the more menial clerical jobs will be replaced by AI systems, for the most part AI will augment the human superior capability to think and judge. A good example is the increasing intelligence being built into GPS systems.

As these systems are able to access more contextual information like traffic conditions, weather and the like, the power to the end user increases. Regular tedious tasks like scheduling group meetings, staff rostering, planning and scheduling will more regularly be performed by AI systems with the ability for human enquiry and override (Siri on steroids).

It's going to be an evolution, more so than revolution.

Rather than treating all data as valid, AI search engines will take into account data quality and adjust their algorithms appropriately.

Learning Opportunities

For example, an AI bot searching for the best air fares will be able to assess the reliability of data feeds it receives form past history, and provide human users with qualified recommendations, rather than current the mechanical ranking that currently exists.

Nitzan Achsaf, Head of Artificial Design Intelligence, Wix

Nitzan Achsaf headshot

Achsaf heads Wix ADI, which learns about you and applies this knowledge to create "the perfect website" for your needs. Before Wix, he managed the product, design and eng teams at Sonicbids (acquired by Backstage) and managed the Next Generation product team at Yahoo Search. He managed R&D teams for seven years., developed strategies at IBM and SanDisk for three years and co-founded two web startups, SafetyNest and ExposeBox. Connect with Nitzan Achsaf on LinkedIn.

It was about time that AI reached the enterprise web. After all, we've been using AI in the consumer web for a long time now. Web search has been based on AI for the past 10 years. Yahoo started that in 2006 (I know that, since I was the AI lead there), and Google moved to use it as well in its search engine about three years ago.

Amazon's product recommendation is based on AI, and if you are an avid user, you will almost feel that it's creepy how it knows you so well. And if you want to watch a movie via Netflix or listen to a song via Pandora, those recommendations are also based on AI. And there are so many other examples from Google Now, to filtering your email from spam, to automatically tagging your pictures based on face recognition to Siri.

AI is here to make our lives easier, and to help us focus on our most important tasks, while removing those things that we don't want or know how to handle.

Tim Wallis, CEO, Content and Code

Tim Wallis headshot

As CEO of London-based Content and Code, Wallis focuses on corporate strategy, client and partner relationships. He has overall responsibility for driving the growth of the company, which he said he founded to help organizations become "more responsive, more competitive and engage their employees to better realize business goals." Before founding Content and Code, Wallis worked at companies including WorldCom, Commonwealth Bank of Australia and Xceed. Tweet to Tim Wallis.

AI will power the next level of productivity in the workplace. Firstly, we'll start with some simple things being automated. For example, diary management. This is a time consuming and expensive task that frequently involves a lot of back and forth.

The majority of our diaries are stored electronically now, typically in Microsoft Outlook, so we can use a digital assistant such as Cortana to find mutually agreeable times for all parties to a meeting, book appropriate rooms, resolve conflicts and reschedule meetings as required. In addition, Cortana can automatically talk to mapping applications and sites to work out the best transport options (and update them as things change).

Then when we are preparing for the meeting, Cortana will collect all the notes from prior meetings, gather relevant emails or other documents. Plus, Cortana will go to LinkedIn and highlight relevant information about other attendees, such as mutual colleagues so you can build better rapport when you meet.

We will also see increasing use of AI and machine learning to improve customer service. We can automatically read emails, tweets or other inbound messages and automatically create replies using predetermined rules so that a human can do a final check and then send out.

For example, think about the millions of emails train companies receive asking for ticket refund due to delays and cancelations, the email can be scanned for date and destination, then the system will automatically check to see if the train was late (and by how long to calculate the refund) and create the response. This would save a huge amount of time.

And this won’t stop at customer service, we can already use AI and machine learning to help improve our win rate for sales. When a new lead or opportunity is input into our CRM system, we can push this lead information to Microsoft Azure and this will recommend the best sales person to deal with that particular enquiry, based on previous wins and losses in similar situations.

AI will be the next power fuel in the enterprise as it will provide competitive advantage in terms of better productivity, better customer service and better sales win rate. AI will be like the modern computer-powered industrial revolution.

Title image by Julia Komarova