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

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

• Target CEO sees an omni-channel retail 'new normal' on the horizon, but there are tough times ahead - Target was a pandemic retail darling, but as Stuart has chronicled, it's been muddles and troubles in the Vaccine Economy. The latest? New omni-pursuits: "One ongoing success story of Q4 was Target’s execution of same-day services - in-store pick-up, Drive Up, and Shipt - which represent more than ten percent of total sales, and which increased 4.3% in the quarter."
• Autistic burnout - a checklist for employer responsibilities - Cath continues an important series: "Last, but not least, meanwhile, is finding ways to create a psychologically safe enough environment for people to feel they can disclose their diagnosis and discuss their needs in the first place."

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

• Salesforce strikes back with strong full year numbers, efficiency focus - and little bit of help from Oracle's Larry Ellison! - Just when Salesforce appeared to be on its heels, it fights back with one of the few things "activist investors" understand - numbers. As Stuart explains, it's about a shift from growth to "efficiency," though there is more to it. Watch this space. Also see:  Madeline's Salesforce invests $1m in Black-led non-profits to close the racial funding gap.
• Workday beats Wall Street Q4 expectations, looks to a return to stronger growth as economy improves - As Stuart reports, Workday also surges, but not without warnings about an "unpredictable" macro environment.
• Zuora CEO Tien Tzuo - buyer behavior is stabilizing despite ongoing macro-economic pressures - Why is Zuoro a bellwether? Because as Zuora goes, the emerging "subscription economy" goes. Via Stuart's post, this quote from Tzuo sums up the overall state of enterprise buying well:

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:

• Demandbase continues to expand beyond ABM with additional services and features - Barb
• No more integrating walled gardens - Contentstack adds front-end hosting to its composable digital experience platform - Barb
• Cloud Software Group one year on - theories are easy, realities are more complicated -  A year ago, Martin ruminated on what would result from the "coming together" of Citrix and TIBCO.  So where are we now?

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:

• A passage to India - the essence of Zoho - Brian
• Are we paying the hyperscalers too much for public cloud? Zoho thinks so - Phil (bonus: interesting reader comment thread)
• Why refrigeration company Cimco put a $1 million quote on ice and turned to Zoho CRM instead - Phil

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

Best of the enterprise web

My top seven

• Amazon Workers Are Fighting (Each Other) About Office Return - return-to-office policies are not one-size-fits-all.
• 5 Quick Ways to Reduce Exposure and Secure Cloud Data - We can stop sharing these checklists whenever companies stop getting breached...
• Why do 20% of software services partners end up winning 80% of the work? - What sets services partners apart? Bonnie Tinder of Raven Intel looks to the data.
• The Beginnings of a Buying Checklist - A checklist for enterprise buyers is past due. Hank Barnes thinks he's honing in: "Top partners are able to prove their track record of success and can credibly point to projects and delivery metrics that show they’ve done it, and can do it better than their peers."
• As industry lauds 5G potential, businesses will need to justify investment - instead of punting the hype to 6G, how about this in-depth review of 5G use cases and adoption?
• AI cannot predict the future. But companies keep trying (and failing) - this post is backed up by a very thorough study: "The entire category of AI tools that make decisions by predicting an individual's future is likely similarly flawed and warrants caution."
• Reimagining people development to overcome talent challenges - How about this zinger from McKinsey? "The problem? Offering formal learning to address skills gaps is not enough because just 10 percent of corporate learning is effective."
• Bonus - two podcasts, via the radical AI podcast, both instructive. This one more on ChatGPT's limitations, the one more on its potentials (the Jungian therapist use case is fascinating)

Whiffs

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.