According to LinkedIn, AI leadership skills are the new must-have leadership skill. Apparently, there’s a surge in people in leadership roles listing prompt engineering and use of generative AI tools on their profiles.
As ever, LinkedIn is less forthcoming on what this actually means – other than it is A GOOD THING!
Whether this represents the latest claims by the career-hungry and ambitious, based on having once asked ChatGPT a question, or something more meaningful, we don’t know. But given the hype and panic about AI, I can imagine many in leadership fearing for their future careers – desperate to appear at one with the zeitgeist. To be a Gen AI Luddite is unacceptable in a world seduced by the potential productivity power of AI.
A fan of the tech, but wary of the hype
Now, I should say I’m a fan of generative AI and its potential to reframe work. Not being hungry for advancement or promotion, I haven’t updated my profile. I’m too busy building AI tools to assist learning and helping others demystify what seems like a scary/exciting/confusing (delete as appropriate) change to their working environment.
But I am cautious of these claims. I do think that leaders need to be abreast of generative AI development. They should be working with their teams to identify use cases, experiment, and build any valuable outcomes from those experiments into their working practice and that of their teams.
The problem with top-down tech adoption
Note that I use the phrase “working with their teams”. Many technology enhancements to work have foundered because:
- No one knows what to do with the tool or what it can do – they just know they should use it for fear of being left behind.
- How and when to use it is imposed on those expected to deploy the tools, without appropriate involvement or consultation.
- Often this is because we choose to introduce the tools with a clear link to a task or activity that needs doing. Spending time building awareness of the tools’ potential and how they could be used is considered an unaffordable luxury. Instead, we provide a step-by-step guide and anticipate that oft-vaunted productivity gains will simply follow.
Unfortunately, introducing new technology and ways of working to a group without a clear understanding of potential, direction of travel and consequences creates a cadre of saboteurs. They’ve read the horror stories about whole swathes of workers becoming surplus to requirements in this brave new world and – not unreasonably – they’re protective of their role and future status as employees.
Bridging the gap in AI leadership skills
LinkedIn suggests there’s a much lower level of engagement with generative AI among those without leadership positions. Leaders are 20% more likely to add AI skills to their profile than the rest of the workforce. Against this backdrop, I worry that AI imposition is more likely than a considered adoption of these tools.
In L&D, we have a role to play in bridging this gap – providing a more general introduction to the potential for responsibly used AI among those for whom it’s currently “something those tech-bods do”.
Furthermore, C-suites are potentially to blame. While senior teams apparently rank AI skills as a top-three skill set for executives, in four out of ten cases, they also believe that their leadership team (presumably without those skills) acts as a barrier – slowing AI adoption in their organisations.
This may explain the earlier claims made by those polishing their CVs. The potential for advancement seems more of an incentive than genuine enthusiasm for, or an increase in, generative AI skills.
Corporate ambition vs real engagement
What the inhabitants of corner offices in corporate HQs want to do with AI isn’t explained in LinkedIn’s announcements. Given that many of them have someone to open their emails for them, I suspect their engagement with the nitty-gritty of any technological breakthrough is patchy at best.
How many of them have imbibed the claims from the world’s consultancies and think tanks about cost savings, reduced staffing, and higher productivity per individual? How many have considered AI through the lens of their workforce?
A people-first approach to AI strategy
This is another role for L&D and the wider HR community. Assessing readiness to engage with AI and to change workflows and work practices is an essential first step in introducing a mature strategic pivot in how tasks are executed.
The wider context for AI adoption should be central to the work of people teams. If left to the tech team, we risk a techno-centric strategy – one that potentially fails to address people, confidentiality, privacy, IP protection, copyright, or any of the other concerns rightly raised in relation to AI.
AI is a potential force for good. It is not, however, without its challenges. While I endorse LinkedIn’s drive to encourage broader understanding of generative AI, the potential for people doing things differently – and doing different, more valuable things – can only be realised alongside, and in step with, governance considerations and long-term implications for the changes we seek to make.
To do anything else is to repeat many of the mistakes made when other technologies were introduced – from the Spinning Jenny onwards.
Postscript: Claude’s take
I thought I’d check my analysis by asking Claude AI to give its take on the LinkedIn statements.
(Note to self: must add prompt engineering to my LinkedIn profile.)
It added some interesting insights:
- There is a 17% increase in job roles advertised which mention AI.
- Sixty-six percent of employers won’t hire someone without AI skills.
- Only 39% of employers provided AI training last year – and only 25% intend to this year.
- The divide in AI adoption risks creating new workplace inequalities if not carefully managed.
Claude also made some recommendations:
- Formalise AI training programmes: Close the gap between leadership expectations and employee capabilities.
- Create AI champions at all levels: Identify and support AI enthusiasts throughout the organisation who can drive adoption among peers.
- Address fear through transparency: Communicate clearly about how AI will augment rather than replace jobs.
- Measure AI impact inclusively: Evaluate AI’s contribution to productivity and job satisfaction across all levels.
- Integrate AI into career development: Make AI proficiency a natural part of career progression, with clear opportunities for growth.
Looks like we’re going to be busy in L&D.
