A reminder that there is almost no case in which Gen AI would have a visible impact on performance in most large firms less than 14 months after GPT-4. Firms don't move that fast, and systemic change takes time. We are in the R&D, experimental deployments, and making bets phase, so we don't have a lot of public data. However, if these McKinsey survey answers for cost savings and revenue gains from Generative AI in 2023(!!) are anywhere close to accurate, it suggests that, even in the limited form and capabilities of current systems, investment is likely just starting.
It’s unevenly distributed so this masks the early movers here. I have a huge amount of clients barely moving past the playing stage, not even convinced they should build anything (or worse, waiting to ‘see what happens’). I have a tiny amount of clients who’ve just ‘built stuff’ in a number of weeks and already seeing the gains in production efficiencies. This will completely change how we build products, it’s just not here yet for everyone.
Tim Miner
3w
Two things you have quoted Ethan Mollick: 1.) The next $Billion corporation may just have 20 employees. All other tasks can be outsourced to AI. 2.) The AI power that large corporations have is the same that small startups have access to. By leveling the playing field, enterprises will see competition at their core very soon. Same service, at half the cost and at twice the speed. Dinosaurs will stumble.
Despite the noise from high-tech corporations, startups, venture investors, and analysts, we are still in a very early phase of generative AI. As a result, it is hard to assume, let alone declare, that generative AI will transform every business process driving operational efficiencies, create new revenue streams, result in massive productivity improvements, and curtail costs. However, the early signs are adequately encouraging for corporations to allocate budgets and start pilot projects. https://corporate-innovation.co/2024/06/25/where-are-we-with-enterprise-ai/
Also like blastoffs with jets the already architected roadmapped and frameworked for pronged phases of coalescing converging opportunities will be the well engineered jets simply awaiting their blastoffs and take off they will. And don't expect those organizations to so much be sharing all these details or their progress as that's how when it becomes apparent they emerge with year plus instilled competitive advantages first mover advantages all the positive cascades and so forth that take years if ever to recover from. Which brings up the question who exactly wants to wake the days where dots connect and competition is years ahead?
Roy Murphy
3w
From what we see this is correct. It takes time to align strategic aims with practical application. We’re in the initial use case phases it’s lots of areas. Most productive areas we see include people management, faqs. Analysis of consumer/internal data (classification then generative in prediction, personalisation) and marketing.
Jay Small
3w
I'm trying to connect the dots between categories such as "risk, legal and compliance" and "human resources," and ANY meaningful revenue gains from the implementation of AI (or anything else, for that matter). Expense savings I get. But unless you're a law firm, for example, how do you increase revenue in risk, legal and compliance?
There's a common challenge among clients where they're finding themselves with increasingly high numbers of internal AI Proof of Concepts but with little defined in terms of path to production. Including a lack of planning of how you actually implement and embed these new capabilities through business design and change. So I agree completely, there's definitely a lot of experimentation on an individual and team level, but it's still early days when it comes to seeing genuine AI driven transformation realised! There is a lot to come yet.
Not sure how surveyed companies quantified both cost reductions and revenue increases! I personally do not trust such surveys.
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3wWhy do you think in HR the differences are the biggest? Is HR „more“ adaptable? And also are there any indicators on how usage of genAI influences the stress levels of people using it. My hopes would be that people will save a bit of time that frees them up for being able to think again isntead of rushing through… if you have any insight on if this is something you see happening in corporates?