Why a Skill-based View of Work is Essential to Implement AI, Part 4

AI Landscapes: Redefining Commerce, Careers, and Communities - Article 4 of 8

One fundamental difference about the AI disruption is that it is happening against a backdrop of a stagnant workforce. The National Bureau of Economic Research reports that 62.7% of the workforce is participating, a drop from 66% twenty years ago. Workforce issues are commonly cited, such as difficulty hiring qualified workers, reduced capacity, obstacles to expansion, and productivity loss. These issues aren’t going away. We will need to learn to live with these new constraints.

The answer is found within the problem. Much has been written about the estimated efficiency gains that AI can produce. AI has also been found to be incredibly useful in speeding onboarding processes and helping staff perform at competency levels faster. AI implementation and workforce issues could mitigate each other.

We’re excited about this opportunity, and it’s altered the way we think about this disruption cycle. In the past, it was always possible to shed roles that could be automated in full or in part and hire in new roles that an organization needs. We believe that the new reality is that hiring for these roles won’t be possible for most organizations and that competitive advantage will accrue to those who ensure their workforce can learn, unlearn, and pivot roles quickly.

I want you to imagine a guy named, “Nick,” who works as a claims adjuster for a large insurance company. Nick is reliable; he shows up on time, doesn’t complain, and generally does a pretty good job. You have no issues with Nick. You find out that leadership has decided that all claims adjustment tasks will be automated by AI by the end of 2025. If this is your reality, do you let Nick go? Absolutely not. It’s hard to find people like Nick, and considering the time and cost it takes to recruit and onboard someone else, who, let’s face it, is an unknown.

You have a lot of people just like Nick, and all of them can help your organization today and tomorrow, but perhaps in a different way. So, what will we have Nick and his fellow claims adjusters do? The answer lies in assessing the current capabilities of our insurance underwriters and understanding the work environment; what does Nick actually do all day, and how does he spend his time? What skills make Nick and his cohorts good at being claims adjusters? Things like active listening, maintaining accurate communication, and ensuring quality information may be found in this process. All of this can be uncovered using a skills-based view of work, as this graphic shows.

Furthermore, as we explore and further understand a skills-based view of work, we can start to see where these claims adjusters might fit into this new reality. Consider how these skills and understanding of core functions at your company could be transferred to other positions. Five years ago, it would have been unthinkable to migrate claims adjusters to QA testing roles in IT. Nick might not even be aware that the skills he applies daily could make him successful in other roles. Although this was always true, we now know how AI can support staff migration from one role to another in a way that wasn’t possible before. The technical knowledge of a role, like QA testing, can, in many ways, be performed by the technology. What is lacking is the business context and human skills that Nick can bring to the role.

We used to have people doing processes supported by technology. This required the people to have the technical knowledge. We’re moving into a world where technology will do the process and be supported by humans. This shift opens incredible possibilities for your workforce.

This series will explore four steps we believe you should be taking – now.

Diagnose and Futurecast: AI isn’t coming. It’s here. Involve your staff – especially those in roles with a lot of human capital – in assessing use cases to boost their knowledge of what is possible and demystify the nature of the change. We now know enough to futurecast roles and understand what they will look like in an AI-enabled world. We can be precisely wrong but directionally accurate about the next five years to develop a plan for how our workforce will change.

Reskilling Human Capital: This country has never experienced a technological shift against a declining labor force. Add to this that AI-experienced resources you might want to acquire will be limited and in very high demand. Just like back in Y2K, hiring your way out of this change will be hard. We must embrace a skills-based understanding of future roles and alternative paths for impacted people.

Content, Education, and Change Management: Change management was huge in the 1990s, and it’s time this discipline came back into fashion. We’ll discuss why acting to control the narrative is crucial and share some ways to do this effectively.

Reimagined Operating Models: All past disruption winners could reimagine a product or service leveraging technology to change the dominant operating model of the day. Uber & Lyft with taxis and Netflix with video streaming are great examples of changed operating models equating to success. We’ll explore how this can be done in a way that reduces risk and can provide speedy returns.

Over this series of eight articles, we’ll touch on all these paths of success to prepare you, your business, and AI's evolving impact on the workforce. Thanks for reading. Let’s talk AI implementation. Send me a note at wade@batonglobal.com.

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About Wade Britt‍

Wade Hampton Britt, IV is a partner and the Managing Director at Bâton Global. He has lived and worked in a dozen countries in the global express and edtech sectors before joining Bâton Global in 2016. Wade is passionate about helping clients and their communities navigate the AI disruption better than previous technological changes.

My sincere thanks to Mike Kritzman and his company, SkillNet, for being my partner in crime with all things skill related.