AI’s largely untapped potential, however, lays in back office operations - not as much in complex problem-solving work environments but in repetitive B2C or B2B transactional environments, where chat-bots can answer common customer questions on a company website, or call-center systems can guide customer interactions through automated responses.
A common misconception - borne from the common reality of robots replacing people in a production plant - is that investing in and adopting AI for routine back office functions will cost jobs. That’s not necessarily the case in practice, however.
“In many cases, instead of using AI as a means of eliminating headcount these companies are simply shifting their focus to finding and retaining additional, highly skilled personnel to work in areas where customer interactions cannot be automated or where more critical thinking and problem solving is commanded.”
One financial services company, for instance, focuses its AI initiatives on improving the effectiveness of its existing client-facing personnel. The organization provides these personnel with a “knowledgebase” populated with answers to previously posed questions/problems to streamline their customer interactions. At the same time, AI technology helps borrowers who prefer an electronic channel interface or who want to transact business outside of normal contact center hours. Sophisticated modeling solutions provide answers to complex multi-variable problems and the knowledgebase is updated and deployed to serve both internal agents and customers.
Though most organizations do expect longer term efficiency gains and cost reductions from AI, in the near term they see it as a tool for improving the end user experience. And while organizations in the telecommunications, financial services and hospitality sectors, for example, are increasingly leveraging AI for transactional tasks, they’re finding that AI is actually reorienting their back-office hiring strategies.
In many cases, instead of using AI as a means of eliminating headcount these companies are simply shifting their focus to finding and retaining additional, highly skilled personnel to work in areas where customer interactions cannot be automated or where more critical thinking and problem solving is commanded. Additionally, managing and maintaining these AI systems requires expert staff.
Implications for CRE
Because AI adoption facilitates the emergence of a new breed of employee it is also portends changes to the physical workplace, to the space they work in. For instance, employees who engage in problem solving – customer service reps with a deep base of knowledge, or nurses answering calls for a medical transaction company - will work more effectively in a collaborative space than in a 50 sq.ft cubicle.
“The fact is, in the world of AI, Corporate Real Estate and Facilities Management teams need to take a fresh look at the type of space they’re dedicating to their personnel.”
AI’s impact on space management, from the afore-mentioned financial services company’s perspective, is two-fold. First, in order for the company to successfully recruit and retain the talent necessary to develop, deploy and support its AI initiatives the workspace it provides needs to be convenient to urban centers, where millennials want to live. Secondly, the space itself must offer open and collaborative work areas along with smaller quiet rooms for conference calls or confidential discussions.
The fact is, in the world of AI, Corporate Real Estate and Facilities Management teams need to take a fresh look at the type of space they’re dedicating to their personnel. While the need for ‘cheap space’ for people who handled transactional processes will decline, the demand for conference rooms and space conducive to problem solving or special cross functional teams will increase. Likewise, in the area of Facilities Management, AI is central to smart-building technology and is beginning to replace security guards and receptionists.
The full scope of AI’s impact on CRE is just beginning to be understood. Generally, when asked their view on AI and machine learning and its impact on their business most at the C-suite level answer that they are studying the topic very seriously, while a large percentage of CRE and department-level managers either haven’t contemplated the question at all or have only scratched the surface in answering it.
Below are a few other fundamental questions every manager and decision-maker should be asking as they begin exploring AI:
Are there certain parts of your business where you believe AI could improve your performance?
What is a realistic and applied approach to implementing AI (in its current nascent state) with respect to workflow and workplace effectiveness?
Do you know of any best-in-class examples of peer companies you believe have implemented a successful AI strategy?
How much time do you spend outside of your four walls learning about the world of AI?
How concerned are you that your job someday will be impacted by this technology or innovation in general?
As already mentioned, C-level executives are closely examining AI and questioning its impact on their company’s competitiveness. For their part, CRE decision-makers - who have always stood at the confluence of space management, people management and technology – are beginning to feel the landscape shift beneath their feet. Now is the time for them to step up, shed long-held paradigms and learn about AI, because it’s real and it’s changing the face of the workplace.
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