This long-form episode of Wicked Problems is a conversation about how EV and AI adoption share the same communication problem: the people designing and promoting these technologies tend to foreground complexity that users neither need nor value.
Toby Corballis and e-mobility communications specialist Jess Shanahan examine why clearer, more human communication matters—from selling electric cars to introducing AI inside organisations.
Their conversation also moves beneath the messaging. Legacy systems, reactive leadership, weak AI literacy and poorly designed change all shape whether new technology creates value or merely adds cost and risk.
Key themes:
Closing the gap between what organisations want to say and what their audiences need to hear
Making EV communication relevant to mainstream drivers rather than technical enthusiasts - How AI-generated content converges towards sameness and plausible-sounding errors
Cognitive offloading and the erosion of critical-thinking capability
Why legacy automotive manufacturers struggle to move at software speed
The danger of reactive transformation and indiscriminate AI adoption
Shadow AI, data risk, model choice and the need for practical AI literacy
Designing technology that is straightforward without concealing meaningful choice
Chapters:
00:00 - Jess introduces her background 00:40 - How a memorable EV press stunt led to a career in the electric mobility sector 02:04 - What the 49 Collective is and why it matters for women in EV 04:22 - Why EV marketing often misses the mark with mainstream drivers 06:22 - B2B messaging needs to speak to people, not just organisations 08:10 - How AI output can sound convincing while still being wrong 10:28 - Cognitive offloading - what happens when AI does too much thinking for us 16:06 - Legacy automotive versus newer EV brands and their very different structures 17:28 - Why modern EV companies can iterate faster with software-style operating models 18:55 - Why legacy manufacturers are pushing for more time and more regulatory flexibility 21:06 - Why people, not just process, determine whether transformation succeeds 22:27 - Why piling new technology onto old systems often fails 23:01 - Why the ICE vehicle fleet means legacy businesses cannot simply be switched off 24:29 - Why reactive companies chase quick wins instead of building a stronger strategy 27:06 - When AI is the wrong tool and why risk tolerance matters 29:26 - How uncontrolled internal usage drives token bills through the roof 31:50 - The problem of shadow AI and accidental data breaches 32:49 - AI literacy requirements and why boards cannot claim ignorance 33:41 - Jess on training organizations in AI risk, prompting, and output checking 35:11 - Model drift and the challenge of choosing the right AI model for the job 38:39 - Should AI interfaces be smart enough to choose the model for the user?
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