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Enterprise hits and misses - Target flounders, Salesforce rebounds, and generative AI gets the enterprise use case review

Jon Reed Profile picture for user jreed March 6, 2023
This week - Microsoft's Bing bot is flawed, but is enterprise search another matter? Enterprise software bellwethers turn in their earnings, with mixed reviews. Target's omni-triumphs face the headwinds, and in the whiffs, Zuckerberg downshifts the Metaverse.


Lead story - Microsoft's Bing bot is a search loser, but is generative AI an enterprise winner?

Nothing like a nice long train ride for a cathartic tech skewering. This time around, I turned my attention to ChatGPT, or what it became as Microsoft's Bing bot: Microsoft's Bing ChatGPT search bot is still looking for answers - but is AI for enterprise search worth a look?

Why portray Bing chat as the future of search, when generative AI is anything but? Generative AI has a number of fascinating use cases, but consumer search, trained by the disinformation cesspool of the open Internet, doesn't look promising.

Microsoft doesn't exactly live up to its "responsible AI" self-billing here. Still, the generative AI cheerleading club isn't bothered:

No problem, the generative AI fans say - all we have to do is keep scaling the training data and the compute power, and ChatGPT will be brilliant. Bonus: we''ll be well on the road to artificial general intelligence. I don't see it that way.

But when we turn our attention to the enterprise, does generative AI create possibilities? I think so. Could enterprise search be one of them? As I wrote:

I found myself at an analyst event with SAP leadership this week, including Executive Board members Thomas Saueressig and Juergen Mueller. With data experts inside and outside of SAP around me, it was a perfect opportunity to ask: is enterprise search a viable use case? The discussions were fascinating, with plenty of talk about the obstacles. The overall view? Yes, enterprise search has potential. But it will come down to the caliber of the data set, and how it is modeled.

I'm not down on ChatGPT. I just want to see use case precision. Enterprise buyers need to know the potentials, but also the limits. Industry is a key part of that. Bring on George Lawton's How Generative AI can streamline medical workflows. Is the medical industry viable for generative AI, where the margin for error can be a real problem? (They don't call it "surgical precision" for nothing). George writes:

The big difference with these new generative AI techniques is that they can automate translating and summarizing information for different audiences based on the doctor’s conversation with the patient. This reduces the need for a secondary dictation process after the visit.

But can this help doctors be better doctors? As George explains, there is a huge disadvantage to waiting hours to document patient interactions, after a long medical shift. Why not involve patients in the documentation itself?

This new approach also has the opportunity to include the patient in the documentation process as a participant rather than someone who is talked about after the fact. The new tools also provide a consumer portal for delivering summarized patient notes. Patients can look at the summary and then play back what the doctor said in the exam room when they do not understand something. This allows the patient to go over what was said and the words that went with it in great detail.

Then again, generative AI's accuracy shortcomings can limit the scope of shorter-term use cases:

Teams need to give participants a chance to review these summaries to ensure accuracy and minimize the impact of AI and human error on others.

Certainly in a healthcare scenario, humans would have to be in the loop - even in basic transcription scenarios. This doesn't rule out generative AI, but it does complicate ROI, as we must factor in the human effort in supervising the machines, and correcting inaccuracies.

The other thing we shouldn't lose track of? The many other ways AI-in-production is already impacting us. To that end, Neil addresses the issue of AI ethics and risk management in NIST's AI risk management framework - is this a way forward for AI ethics, and trustworthy AI?

Diginomica picks - my top stories on diginomica this week

Vendor analysis, diginomica style - enterprise earnings blowout. Let's start with the bellwethers:

While the uncertainty we saw in buyer behavior at the end of Q3 has not disappeared, it certainly has lessened. Even as companies settle into this extended period of higher interest rates and lower macro-economic growth they continue to prioritize digital transformation. They continue to launch and scale recurring revenue businesses and they continue to pursue growth and new revenue streams through these new digital services.

More earnings news to digest: Box FY23 Q4 results yield cautious-but-positive outlook, Levie looks to enterprise LLM use cases (Phil),  and Samsara achieves ‘Rule of 40’ for two quarters in a row as it heads towards $1 billion ARR (Derek).

A few more vendor picks, without the quotables:

Zoho hosted a very unique and adventurous analyst event - a small group of analysts, including Phil and Brian, made the trek to India to get to the essence of Zoho's culture (and business model). Zoho did a good job of avoiding excessive NDAs (hear that, vendors?). As a result, there was deep coverage of the event, including:

Also, Derek welcomed new diginomica partner Pure Storage into the fold.

Best of the enterprise web

Waiter suggesting a bottle of wine to a customer

My top seven

Overworked businessman


Super-fun headlines this week - this one is actually eco-legit, but still: King Charles III's Coronation Oil Won't Contain Sperm Whale Intestinal Wax. Interesting safety tips from the US National Park Service:

LastPass deserves all this and more:

Maybe a name change to NotYourLastPass would be apropo also? CNET is back with its awesome new business model:

Fans of SEO-optimized content bots rejoice. Meanwhile, is this a fireable offense?

I'm not a fan of firing people willy-nilly, but this is just egregiously goofy. Students are waiting on a coherent explanation as to why this was the right email for the ChatGPT treatment. Finally, my old stomping grounds:

Isn't it fascinating how the real next big thing makes the appointed next big thing look phony? See you next time...

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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