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Enterprise hits and misses - retailers buy in on generative AI, but where are the use cases? AI projects yield lessons, but burnout needs attention

Jon Reed Profile picture for user jreed August 21, 2023
This week - retailers talk up generative AI, and we evaluate the possibilities. Enterprise AI project lessons come into focus, but other issues loom - from risk management to employee burnout. In your whiffs, I blow a gasket and ask: can we get rid of CAPTCHAs?

King Checkmate

Lead story - Retailers buy in on generative AI - but what are the use cases?

Retailers aren't going to miss out on the generative AI opportunity, but what is that opportunity exactly? Stuart digs in, via Can generative AI help Walmart to be who it wants to be? CEO Doug McMillon thinks so. Stuart's problem statement: 

Walmart e-commerce sales are up 24% year-on-year, but still not showing a profit. Will generative AI make a difference in boosting digital margins?

Walmart CEO Doug McMillon played a card we've been seeing a lot lately: the 'our customer data will give us a generative AI advantage' card. Stuart quotes McMillon:

Our data assets are unique, and we're excited about the potential to leverage them in new and impactful ways. We're taking Large Language Models developed by our partners and by the broader tech community and adding retail context to create models that are uniquely suited to the needs of our customers, our associates and our supply chain.

McMillan goes on to cite "personalization" and the Walmart+ loyalty program as two areas where generative AI shows promise, via more pro-active engagement. While I agree that opt-in customer data, properly applied, can be a formidable enterprise asset, the use case details look vague at this juncture. I've explained before: I don't like 1:1 personalization as a generative AI use case.

Sure, no one will be physically harmed if you get personalization wrong, but generative AI (or any other AI predictive tool), simply isn't accurate enough for persuasive 1:1 personalization. The chances for a foot-in-mouth personalization gaffe are just too likely (example: 'We're looking forward to seeing you and your wife again at our resort soon', when wife is in hospital etc.). The money question is: can generative AI aid in creating (and serving) more personalized segments? (Example: identifying a pattern such as weekend lawn care shoppers, and serving up personalized offers and content to those customer segments). That sounds promising to me, but the ROI remains to be seen.

Call me a cranky, old fashioned old schooler, but to me, the big Walmart edge is the omni-channel store/online fusion. Stuart quotes MacMillon on this:

Our stores and clubs give us a competitive advantage and power our omni-channel model. Our curbside pickup business continues to grow as people look for ways to save time, and store-fulfilled delivery is now growing faster than pickup across all three segments.

Generative AI use cases will sharpen, but for now, that omni-channel edge is the more persuasive advantage. We get more clues via Stuart's AI and online retail - learnings from Etsy CEO Josh Silverman. He quotes Silverman:

We've made incredible gains in relevance. Now we understand what you meant, not just what you said. So if you come and you type into a search engine, 'cocktail attire for men', we're going to show you mostly sport coats. Even though the words ‘sport’ and ‘coat’ did not appear in your query, we understand what you meant. That's an example of neural network translators.

Yes, that's persuasive; we know that AI for e-commerce is a proven sales uplift. One minor quibble: that's a deep learning benefit, but that use case was viable before generative AI came along. Silverman is confident that generative AI can plug in here also, including having "better conversations" with consumers about what they need - but alas, that's going to be a familiar theme this fall: lots of confidence in generative AI, with specifics not yet fully baked.

diginomica picks - my top stories on diginomica this week

Vendor analysis, diginomica style. Here's my three top choices from our vendor coverage:

A couple more vendor picks, without the quotables:

Jon's grab bag - Chris nails down enterprise attitudes towards AI, with fresh data to parse: Enterprises have little idea what they are buying with AI – but that's not going to stop them! “'I’m worried about AI, but simply must have it!' is the mantra of the day," writes Chris. Yikes, but true. Neil probes AI's impact on the insurance industry in The insurance implications of AI are heating up - reviewing the NAIC's Model Bulletin for the use of algorithms and AI. Finally, I pulled out the video content barbs and wisdom from my recent video show with Brent Leary: B2B video strategy needs a rethink - so much potential, so much stale output.

Best of the enterprise web

Waiter suggesting a bottle of wine to a customer

My top seven

One of the offshoots of GenAI is its use with developer productivity – code generation type use cases . Everyone – me especially – got very excited when we saw the possibilities for the first time. But that doesn’t naturally translate to the enterprise world – IP problems come into play very quickly. GenAI is only as good as the training set that was used in its creation.

Overworked businessman


I blew another gasket while slogging through my post-vacation inbox:

Oh, and I flipped-flopped on generative AI a bit:

So... does this mean we can get rid of CAPTCHAs?

If you find an #ensw piece that qualifies for hits and misses - in a good or bad way - let me know in the comments as Clive (almost) always does. Most Enterprise hits and misses articles are selected from my curated @jonerpnewsfeed.

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