Today's technology boom is predominately around Artificial Intelligence (aka Ai), Robots (aka Bots), Algorithms (aka software formulas) and Apps (aka Software Applications). And, for good reason. These technologies are becoming massive industries in and of themselves, driving incremental value via cost savings to an organizations bottom line. They are changing how we work, or if we work.
So, what is driving the deployment of this technology? The never ending drive to increase revenue and decrease costs. (aka Capitalism). Human capital is the most expensive line item on every budget. The last time human capital received this much "cost cutting" attention was the early 2000's, during the internet and outsourcing boom - leveraging the internet as a global distribution platform to move volumes of critical labor to lower cost countries.
Some of the newest applications, robots, algorithms and software deployed over the past two to three years had one goal: To Replace Humans to Cut Labor Costs and Taxes. This trend is growing. But when will we hit the "tipping point?"
Based on my interactions with a number of executives and I.T. experts across multiple industries, I've witnessed some critical barriers to widespread adoption of these new technologies for the near future (3-5 years):
1. Lack of A.i. Knowledge, Use Case Scenarios, and Fear of Job Loss. For an organization to adopt A.i., they need to understand its various uses and how to apply it. This is not just what I've witnessed, this is what IBM says as well. It will be large organizations who adopt A.i. first (For example, companies like Target, P&G and Netflix have already implemented multiple A.i. processes). Such use cases did not originate from the top down, but from the middle ranks. Mid level managers, who are close to specific "people based" processes, identified applications and sought solutions within their existing budgets. However, many managers are not trained or skilled in all facets of A.i. technology and how to use it. And, more importantly, there is an innate fear of introducing new technologies which will eliminate their job.
2. Database Disconnect. For most processes that are automated in some way, the processes (Robots) must know where the data resides in order to solve problems, answer questions and provide value. Programmers must connect many disparate databases in order to pull the data necessary to solve a problem or customer request. Normally, this is what a "human being" would do. But, if you want a machine to do the same process, then the machine must know how and where to find answers. (I imagine that databases will continue to move to the large A.i. data storage providers - Amazon, Google, Microsoft, etc.). The problem is a back-end database programming issue more than anything else. It can (and will) be done, but it simply takes time and money, especially for very large organizations who often have many disparate databases. Large organizations have the funds, but often bureaucracy may be the biggest barrier than anything else.
As we know, everything takes time. But, we are talking about robots, servers, processors and computers. They operate at "light speed." So, the lag time is more of the human element, corporate processes, human fears and corporate bureaucracy holding back the "tipping point." But, it will arrive.
If you wish to discuss in more depth how A.I. is impacting the contact center, please contact me via email, steve@emergingglobal.com, or call me, 602-312-8900. We have a host of A.I. and Robot solutions which, when combined with the right live-agent, can save money and improve Net-Promotor Scores (NPS).
Steve Shefveland
Founder
EGS Global, Inc., d/b/a Emerging Global Services
steve@emergingglobal.com / 602-312-8900
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