What I love about SXSW Sydney is that it truly allows you to explore emerging topics in interesting ways. Our proposal to organisers, “Are dogs generative AI’s greatest beneficiaries?” may have sounded trivial but it gets to the heart of a problem faced by many.
That is: “We’ve experimented with gen AI, possibly run a few proofs-of-concept – but now I need to show the value to my [manager, executive team, board, investors or others].” And that leads to both questions on what value organisations are aspiring to, and where that value show up: time to walk the dog, do higher order tasks... or in the enterprise P&L?
I’m extremely grateful for the inspirational panelists that joined me on the stage to explore these questions: Dayle Stevens OAM, Executive Data and AI, Telstra, Nicky Sparshott, Global Chief of Transformation, Unilever, and Catherine Walsh, Chief People Officer, Qantas. Here’s some of what the audience took away.
We’re in a new industrial revolution
Just as the steam engine sped up production, so has generative AI accelerated the rate at which tasks can be completed. The difference is that for the first time in history, those tasks are largely cognitive, not physical – and so highly educated knowledge workers are impacted. Analysis by McKinsey suggest that the overall automation potential of generative AI is highest for those with a Master’s, PhD, or higher.
What does this mean? Now, more than ever, the shift is a question of human capital and leadership.
With big data comes big responsibility, for all
Dayle shared that Telstra is increasing the AI fluency for its entire workforce, not just data and AI professionals. This includes completing responsible AI training before receiving access to tools like Copilot.
Panelists agreed that the approach of giving as many people as possible the understanding of what could go wrong, without having to understand all the technical aspects of AI, was an important step for organisations. This applies from the frontline to the boardroom.
The value then comes not just from the immediate output – faster tasks, more time etc. but also from the mitigation of future risk as the accountability is distributed through the workforce.
The promise lies within people
Catherine’s ultimate responsibility of health, wellbeing, and employment, means any problem starts and ends with people. This means bringing everyone – from pilots, to air crew, to mechanics, baggage handlers, hospitality, the various unions, government, and more – on the journey. And do it simultaneously; because where other significant transformations like digitisation were done over long periods of time, the AI revolution is happening FAST.
But by bringing people on the journey it’s created even better solutions, like dashboards augmented by AI pilots, or the production of mechanics’ tools in days or weeks – not the months that could be lost were they to be sourced through a vendor. It creates value for the right people in the way they need and want. Importantly, they are part of that solution.
We’re not being ‘AI magpies’, simply attracted to the shiney new tech. We’re excited, but thinking about how the technology is being applied to the problem to be solved.
The ‘middle bit’ is HARD
Nicky spoke about giving time back to employees, and to Unilever ANZ’s four-day work week trial, in which the company gave employees in ANZ the opportunity to work 80% of the time, for 100% salary, provided 100% of outcomes were met. This was almost 50 days back in their year to do study, pursue a hobby, give back to the community, keep children out of daycare – whatever. Two key outcomes: profits and wellbeing were up, absenteeism and stress were down.
Getting to this point was not always guaranteed – Nicky candidly shared that there are times, in any big change initiative the intended outcomes can feel far from reach. To her, it highlighted that we can all be great at painting a picture of the ideal end state but the journey to get there can be messy and hard! Keeping focused whilst pivoting as required can be a superpower.
So, ARE dogs generative AI’s greatest beneficiaries?
Reflecting on the conversation, I think the answer is that we are all beneficiaries of this exciting technology, provided that it’s done in collaboration, with the right governance, and well-designed metrics and objectives. In the business context that can be time found, money saved, customer satisfaction improved or reported wellbeing increased.
And if the dog gets an extra walk every now and again, that’s not a bad world to be creating.