Artificial Intelligence -- Not So Artificial
Enterprises today should be analyzing communications-centric workflows in the context of AI-based transformations.
Artificial intelligence (AI) has so much buzz about it, you could think this is something new. It's not. The term AI has been used since 1956 to describe things that machines could do that displayed intelligence.
Of course, AI always has the feeling of being something new. As computing power and software sophistication increase, new and exciting things are made possible. But as each new capability is adopted and incorporated into business workflows and personal use, it falls out of the AI category and just becomes another feature in our products.
The examples are too numerous to list, but speech recognition would be a good one to mention. Twenty years ago, speech recognition was fairly basic with either limited vocabularies or moderately high error rates. Now we have Siri, Cortana, Alexa, Dragon Dictate, and many other speech-enabled "servants" in our lives.
Good with the Bad
For our enterprise communications industry sector, today's AI is both a threat and an opportunity.
The threat is clear and present. Software can do a lot of things that used to require human labor, assistance, or intervention. Examples from the past included direct-distance dialing, speed dialing, interactive voice response (IVR) for self-service applications, speech recognition to enhance the IVR systems, Websites for self-service transaction processing, automated workflows to eliminate calls or email messages, search tools, and many more.
As an example of transformations we're now facing, a contact center may soon become only an "exception-processing center" to assist those customers who can't (or won't) complete their transactions using the automated and intelligent self-service tools. As another example, administrative and operational roles will be reshaped to remove routine or trivial communications steps, whether voice-based or text-based, that are simply the transmission of known information.
Increasingly, most work roles will require skill in use of human-software interfaces to serve customers or to complete a task or transaction. Work across all processes in the enterprise value chain -- design, marketing, selling, production, service, administration, management -- will very likely be aided by AI-based systems. Maybe we'll even have a catchphrase for that, calling it "an AIded position."
The opportunity for AI is less clear and requires innovative action and intense change management. But the opportunity is also quite large. My analysis from 2014 found that as much as 54% of employee time is spent in some form of communication, consuming about 21% of a typical enterprise's revenues. Thus the opportunity is potentially worth trillions of dollars.
If you're an enterprise communications leader, I recommend that you focus on projects to analyze the communications-centric workflows within your organization in the context of AI-based transformations. Use the business analysts in your communications team to lead these analysis projects, in partnership with the business units in which these communications-centric workflows occur. If you don't have business analysts, then consider hiring or subcontracting those skills, since finding and then prioritizing the opportunities for AI-type improvements is urgent and critical.
You might find a framework helpful for this analysis. An inventory of what new capabilities are available and a logical approach to the review and analysis of the existing workflows are important elements of this framework. The capabilities of communications platform as a service (CPaaS) are useful when building the inventory of new capabilities. The disciplines of business analysis or of Lean Six Sigma are useful to support the logical review and analysis activities.
Lead, Don't Follow
When you find opportunities, work with the AI experts in your IT team or with AI-skilled system integrators to provide designs of improved workflows or processes that can then be presented to business unit leaders or department heads for consideration, prioritization, and funding.
Be bold, since many of the AI-type improvements will require significant change. Some of the improvements will actually reduce staffing levels, which is often one of the most difficult types of change for business units to manage. Of course, methods such as proofs of concept or pilot projects can be used to phase in the changes.
But don't be too cautious. This AI-driven type of change is here to stay. Every day, entrepreneurs are looking for ways to apply AI capabilities to reinvent what enterprises do and then to take over that function via cloud-based and mobile-based services. Hesitancy could lead to your organization facing an Uber type of disruption. Leading is far better than following in this case.
Also, you probably can't just wait for the communications vendors to do this for you. AI-type transformations have to occur in the context of the workflows of each organization and within the industry context of that organization. When AI-type breakthroughs are found, each one will likely be considered a proprietary asset of your enterprise, not a generic feature of a communications technology product.
Hopefully, you'll agree that AI is anything but "artificial" intelligence. Algorithmic intelligence, yes; automated intelligence, yes; analytic intelligence, yes. But there's nothing artificial about software that will manufacture your car and then drive it more safely than you can do for yourself.
AI, by whatever name, will be with us far into the future. The magic will come as you rethink most everything you do in terms of how you can get software and computing power to work for you and for your enterprise or organization and then apply this to produce a more fulfilling life in an enriched society.
Learn more about Artificial Intelligence (AI)/ Analytics at Enterprise Connect 2018, March 12 to 15, in Orlando, Fla. Register now using the code NOJITTER to save an additional $200 off the Advance Rate or get a free Expo Plus pass.
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