May Habib’s Post

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CEO of Writer.com | Enterprise generative AI | Hiring in ML, eng, design, mktg, sales + CS

Good generative AI-era CIOs know the market, the players, the offerings — the actual products, not just the marketing pitch. Bad generative AI-era CIOs listen just to the pitches — and they stop at the hyperscalers and strategy consultants. Good generative AI-era CIOs are hands-on with AI — the APIs, the applications, the studios, the frameworks. Bad generative AI-era CIOs use Copilot to draft their emails — and that's about it. Good generative AI-era CIOs are visionaries who paint a future that all employees — not just in IT — get excited about. Bad generative AI-era CIOs outsource AI vision to Big Tech. Good generative AI-era CIOs build AI teams inside of IT whose job it is to serve the business. Bad generative AI-era CIOs build AI teams who develop AI prototypes untethered to business reality or real users. Good generative AI-era CIOs understand that employee adoption is the gateway to value realization and they partner with their CHROs and business leaders to drive adoption. Bad generative AI-era CIOs don't talk to employees outside of IT about AI. Good generative AI-era CIOs have honest conversations with their CEO and boards about when AI will hit the PnL. Bad generative AI-era CIOs haven't talked to the board about generative AI since 1H'2023. Good generative AI-era CIOs run a cross-functional AI taskforce whose job it is to help the organization responsibly, legally, and ethically develop and use AI applications. Bad generative AI-era CIOs run a cross-functional AI taskforce whose job it is to slow things down until "the market settles." Good generative-AI era CIOs deliver meaningful impact to the organization with generative AI budgets of <$5m. Bad generative-AI era CIOs want to commit tens of millions and issue a press release before POCs are actually in production and getting utilization. Good generative-AI era CIOs understand that scaling and managing AI apps and workflows is going to be just as important as building prototypes, and invest in the tooling and resourcing to do that. Bad generative-AI era CIOs build one company GPT and then lose interest after launching it at the company's AI town hall. Good generative-AI era CIOs know the business needs hands-on AI learnings in order to get their heads around the change management. Bad generative-AI era CIOs think it’s all about their model garden architecture. Good generative-AI era CIOs diversify their approaches to building and deploying AI applications. Bad generative-AI era CIOs just swap LLMs. Good generative-AI era CIOs know that the key to high quality, accurate AI apps and workflows is data — and a lot of that data sits in people's heads and desktops, not just in DBs. Bad generative-AI era CIOs don't want to start on generative AI until the 2-year data transformation project is complete. Good generative-AI era CIOs understand that the speed of the disruption is the disruption. Bad generative-AI era CIOs are still trying to catch their breath.

Scott Spradley

CTO, CIO, Board Member

4w

Incredibly well said May. There are so many points here that whispered about, and you have basically covered a guidepost to help those Bad GAI CIOs to follow to add more value to their companies. That said, a key component is being ENABLED to leverage GAI, and many companies may not be prepared due to lack of quality data or an inability to develop strong ML that can be used to learn from it. Great Post!

Simon Small

UK’s top-rated AI Keynote speaker: “600 people became smarter and more articulate in 40 minutes” “best session of the conference” “everyone is talking about you”. SEO-AI Entrepreneur (using SEO as a competitive weapon).

1mo

This ❤️. I am resisting the urge to turn it into LLM lyrics. What I love about it is that it gives us all a window into the breadth of the CIO world as you see it in this moment in time. It shows how many are not grabbing some of the amazing enterprise Gen AI solutions with both hands. Gatekeepers. Comparatively. Enterprise is lagging by a long way, as a whole. I haven’t seen it quantified but maybe Enterprise could be 12-18 months behind in GenAI capability compared to what is proven and available to them. 🤷♂️

Jamie Barnett, CISSP

Advisor and board member. Listener, learner, upstander. Die-hard Monty Python fan.

1mo

Really, this applies to all execs.

MJ Petroni

CEO, Cyborg Anthropologist, Speaker on AI and Digital Fluency

1mo

All of this. Also: Good generative-AI CIOs are actively talking about ethical inclusion of all people in their AI workflows and AI models to prevent discrimination and unintended outcomes, while building AI fluency and informed consent. Bad generative-AI CIOs are getting 'the guys in a room' to come up with the fastest possible way to do AI—without considering the impacts.

Diego Lomanto

CMO @ Writer | Enterprise Generative AI, Ex-UiPath VP Product Marketing, Startup Advisor/Investor

1mo

Spot on May Habib. There's never been a better opportunity for good CIOs to elevate themselves and their orgs!

Enrique Olives

Head of Product Marketing at Vyond, MBA with Marketing Leadership expertise | Salesforce Alum | Golfer 🏌️♂️

1mo

I love this! The good, the bad and the ugly! This applies to all execs and C-suites!

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Jaimin D.

Industry Consulting Leader | Financial Services & Insurance | Driving AI-Fueled Innovation | Helping Clients Achieve Value | Accenture

4w

What a comprehensive breakdown, May Habib Thanks for sharing these insights!

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