Enterprise hits and misses - Retailers hit Black Friday numbers, DevOps gets quantified, and AI projects get real

Jon Reed Profile picture for user jreed November 28, 2022
This week - retailers get a pretty decent Black Friday, but questions linger. AI projects get a reality check, as data on ROI and employee buy-in rolls in. DevOps isn't easy, and neither are open source language models (just ask Meta). As always, your weekly whiffs.

King Checkmate

Lead story - Wrap up warm for AI Summer, or you might catch cold - AI lessons and cautionary tales

As AI adoption continues to surge, burning enterprise questions remain, not the least of which is ROI. A Chris notes in his AI summer piece:

A new report from IT services and consulting firm Infosys reveals that most companies are still failing to convert data science into what they really need: measurable business value.

So how do organizations avoid this? A more comprehensive/strategic approach is in order. Chris:

Among the leaders in AI adoption, the most satisfied are those that have focused on improved data sharing, trust and ethical usage, and integrating data science with their line-of-business functions. This suggests that strategic initiatives in support of clear, top-down aims are more likely to succeed than tactical, hype-led programs.

Chris cites a recent session from the Information Commision's Office:

At the ICO, we see a bright future for AI in the UK, underpinned by terrific trust and confidence in how AI is developed and used. But the actions of an irresponsible few risk undermining this.

"Irresponsible few?" Problematic examples include controversial facial recognition systems, unproven use cases like emotion recognition, and overreaches like Meta's latest open source language fiasco, Galactica (I'll get to that shortly). Leading Chris to conclude:

The lesson is we may be expecting too much too quickly from some AI ventures, while losing sight of obvious risks and challenges. As decision-makers, we need to do better than that, especially when handling the personal data of millions of citizens and customers, many of whom may be vulnerable.

So, we press on. Chris examines a path forward in AI demands a contract of trust, says KPMG. Given the US Thanksgiving holiday, Neil served up a timely argument for why AI can - and should - be applied to food insecurity in Can AI help us address food insecurity and food waste?

Diginomica picks -

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

Customer use case selections:

A few more vendor picks, without the quotables:

Jon's grab bag - Madeline profiled a company that plenty could learn from: ServiceMax shows how gender parity in tech can be done. She also took a hard look at Black women in tech - a UK perspective. Finally, Neil issued an important post on why semantic layers need a rethink: We need a real semantic layer - but something is missing:

Semantic abstraction benefits analytics by moving information integration to a new level, where intelligence can more easily and swiftly proliferate throughout an organization. Productivity will increase because machines will make everyone less reliant on a small number of go-to super-users and help us get beyond today's rigid, often brittle schemas and thin metadata.

Sounds like pretty good marching orders for a BI team near you...

Best of the enterprise web

Waiter suggesting a bottle of wine to a customer

My top seven

Overworked businessman


Another week, another retracted AI open source language model. This time, Meta did the (dis)honors:

Bonus: the I-hope-you're-happy petulance from the lead Meta scientist on the project...  Meanwhile, the breathless search for the next click, err, the next-big-thing continues:

Picked this one up for Neil Raden... Something tells me that a reality TV deal for the next chapter won't be forthcoming...

Oh, and the details on how Alexa loses gobs of money are coming in dribs and drabs:

It used to be fun to mock Alexa; now I worry one day, Alexa won't wake up, and I'll be back to setting manual alarms, and figuring out how to turn music on. All is forgiven... 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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