Premature Excitement - Generative AI and the folly of skipping to the end

Much has been written about the potential impact of Generative AI on the workforce. Last week I attended a conference with engaging presentations from many articulate thought and business leaders. Hypothesis around how work will change, the skills that are required (or not) and the opportunities (and risks) it presents were plentiful.

My presentation, while focused on the broader subject of transformation, building resilience and the implications to people management, also jumped on the Generative AI band-wagon, though maybe in a slightly less excitable way. The key tenets of my presentation were:

• When it comes to transformation - it is the journey that is important, not the outcome. You want to equip people to be able to bounce back AND forward. It doesn’t really matter whether you call that effort: “future of work”, “well-being” or you make it part of your EVP - which you probably should.
• Driving change through the workforce is incredibly complex. Along the journey you will constantly need to balance cost saving initiatives with investments. Tipping too far in any direction will undoubtedly limit your ability to grow or operate effectively.
• Collaboration is the key-unlock. Segregation of duties means we have spent too long in silos so that, when we look to solve, we do so within the constraint of that silo. A rewards person will solve attraction and retention issues with pay (which is expensive, and potentially ineffective). Collaboration can “fully solve” the issue and involves others to consider whether you are hiring the right people in the first place, and how else you are investing in your talent beyond pay.

I would suggest this is standard workforce transformation fodder though... I briefly touched on what the future world of work could look like where:

• companies and employees have a better understanding of their potential,
• the intervention required to understand and realize that potential,
• and the tools to motivate, engage and drive performance.

Generative AI can empower it: sun-setting certain roles, helping people accelerate through the learning curve for new roles, and augmenting tasks.

However, when asked about Generative AI specifically, I suggested we may be guilty of looking at Generative AI in the same half-baked way we often view transformation…

… Namely, because you cannot just skip to the end, and the journey is long and hard, we may end up focusing on the easy – less impactful - option.

The buzz that generative-AI has driven is no different to any other trend. It might last longer than Pokémon Go, but for companies to really benefit from the impact of generative-AI, companies need to consider a balanced journey, that requires collaboration to drive successful outcomes.

Many of my workforce transformation conversations invariably now include the question: “how should we be thinking about GPT’s impact on the workforce”.

And my counter-question is: “what are your foundations like?”

I have spent a lot of my career working in transformation - and have the battle scars to show for it. Based on this experience, I’d take a reasonable bet that most foundations are not set up to deliver on the hype. Yes, we can stand-up specific use cases, probably aimed at targeted types of augmented workflow - such as R&D - but few will take the journey to really reap the benefits of generative AI.

Future Proof Workforce Management:

Let’s take a deeper look at the foundations required to build a sophisticated workforce capable of sustaining the bounce back and forward cycle. The below is a maturity curve that outlines the different levels of sophistication required to drive the future of work, (or resilience / digital transformation etc - remember the destination is just about articulating the purpose).

Workforce Transformation Maturity Curve:

This diagram organizes and articulates several compounding work streams, each with their own workflow. It is not holistic but gives a sense of the journey required to build a future-proof approach to workforce management.

To simplify:

Step 1. Foundational: Documentation and policy. Yes - culture is complex when you see it in action (and could be considered a destination) BUT writing it down as a mission statement, vision, and strategy is relatively simple.

Step 2: Reactive: Data. What data do you have access to? Is it within the context of the broader market (e.g., benchmarking)? How often is it collected? Most firms try to avoid the reality that they do not have an effective data strategy - because they skipped it.

Step 3: Proactive: Structure. Do you have the people structure and architecture in place to understand the connectivity, relationships, job titles, skills that exist in the roles today, and what they could do tomorrow?

Step 4: Advanced: Analytics and Insights: If you have step 1 through 3 in place you can start to realize the ability to inform decision making based on empirical evidence.

NOTE: It is at this point a chatbot might become plausible and useful - releasing the value of the foundational work done and overtime releasing us all from our dependency on “dashboards”.

Step 5: Leading: Is action oriented - entrenching the process, making it the norm. A chatbot, particularly a proactive one that doesn’t need to be prompted, could be incredibly useful in a variety of ways. Imagine if you had access to…

A Strategic People Planning “Co-pilot:” That provides a proactive analysis of the workforce, modelling, and scenario testing changes - a digital partner to inform workforce planning, people analytics and guide decision making.

• Imaginary prompt: “What is the best way to save 10% of workforce cost, without jeopardizing future growth, potential and engagement”?

A careers counsellor that connects employee and employer - helping both understand the potential of their skills, capability and the intervention required.

• Imaginary prompt: “I’ve been thinking about my next move - what are my options and what would be most productive and desired by my company”

A digital assistant to entrench wellbeing, moving us beyond engagement and pulse surveys and making nudge technology more intuitive.

• Imaginary prompt - this one from employer to employee: “We notice that you are working long hours in a virtual environment - and we notice many suffer fatigue and stress from not being able to switch off… Here are some specific suggestions and courses that might resonate with you…”

These are just a few suggestions and there many. They compound and become self-fulfilling if all this interaction is connected into one symbiotic employer/employee journey.

It is not science fiction though, if everything is available, accessible, tailored to the firm, the data is tagged and structured to drive meaningful analysis... This scenario is entirely feasible. However, without steps 1 through 3 you will be stuck with a chatbot that doesn’t have the right inputs to move beyond one dimension. And as we said – workforce change is incredibly complex.

It’s a holistic, entrenched approach to driving change and using a modern technology to make it accessible. But it’s with a foundation that can be built on so that when the next technology gimmick comes about or dare I say, you need to cut cost out of the business… you can do so, quickly, effectively and on an informed basis.

That’s how we achieve the future of work. Chabot, Voice Assistant, Co-Pilot or even who those old enough to remember “Clippy” included.