Enterprise hits and misses - enterprise AI adoption gets quantified, IBM acquires Apptio, and Twitter flirts with self-defeat again

Jon Reed Profile picture for user jreed July 5, 2023
This week - leading enterprise software vendors reveal fresh AI data - but where do we stand on generative AI adoption? IBM acquires Apptio, Anaplan endures layoffs, digital transformation gets (re)constructed, and Twitter does its best to defeat itself.

King Checkmate

Lead story - Leading software vendors weigh on generative AI - but what are the roadblocks?

Salesforce and Workday both released notable AI reports. Unlike most shiny new tech toys, customers are not only high on AI - they are hot in pursuit. As Sarah reported in All in for generative AI, but organizational jitters remain - Workday and Salesforce research airs the opportunities and the challenges:

Workday polled 1000 companies from around the globe for its Insights on Artificial Intelligence in the Enterprise 2023 report. It found that more than 90% of respondents - HR, IT and finance professionals - have already invested in AI, with 99% believing there are real business benefits to be had from using such tech.

As Sarah notes, Salesforce uncovered similar data on the marketing/sales side:

Meanwhile Salesforce surveyed over 2,000 sales and service professionals as part of its Generative AI Snapshot Research Series. Some 61% of sales people believe generative AI will help them serve customers better, while a similar percentage reckon it will help them to sell more efficiently.  Among service professionals, nearly two-thirds (63%) predict generative AI will help them to serve customers faster.

Oracle had themselves a busy AI week also. I dug into that in Can generative AI make HR more productive - and less biased? A closer look at Oracle's HCM AI announcements:

As so-called "Shadow AI" makes fast and unsettling inroads, with risky potential consequences on data privacy, customers want something better. They expect their trusted vendors to deliver this functionality.

The survey data backs this up. AI may be hot, but it's not to be trifled with either. Sarah's calls attention to adoption:

But, that said, adoption rates remain low - 35% of sales respondents, 24% of service. That’s considerably lower than some other business functions. For example, Salesforce’s research cites 51% of marketers using generative AI. That gap looks likely to continue.

Why the disconnect? In my whirlwind spring tour, I found the adoption reasons cited here, and more: risk/liability management, skills gaps, and ethics/trust. However, with all the lovely talk about generative AI, very little of it is actually shipped in generally available enterprise products right now. The guardrails we are anticipating should boost adoption, but that will come when products ship. For now, I agree with Sarah's point on data readiness:

As with all systems the quality of the data being used will have a big impact on the effectiveness of AI platforms, and 77%of the respondents to the Workday survey felt that this could be a large stumbling block for their organizations. Having an overlying steering committee, like Mastercard has, that looks at data integrity is one way of overcoming this issue.

Can "AI" solve itself here? Can AI help in the laborious aspects of data cleansing - including so-called "federated" solutions that allow the data to reside where it currently exists? To a degree, yes - though I'll point out that in many industries, there is gold in hard-to-wrangle unstructured data, or data in shop floor machines that doesn't communicate nicely, at least not yet.

Just because customers want AI doesn't mean they fully understand what it's good at - and what it's not. Particularly in higher stakes use cases with legal or human consequences (Oracle was a good sport on my pursuit of those questions, when it comes to HR). Vendors can  - and should - do a better job of spelling that out. Clarity won't hurt sales - there is no risk of any loss of interest. I have some problems with how AI is positioned right now, but the level of customer interest can't be quarreled with.

Diginomica picks - my top stories on diginomica this week

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

Snowflake Summit 2023 - Mark Samuels was all over our Snowflake Summit coverage. My highlight quote pick, from the surprisingly-titled Snowflake Summit - why founder Benoît Dageville was disappointed by the rise of ChatGPT:

Dageville says the ongoing refinement of Snowflake’s Data Cloud and the features the company provides to its customers should go a long way towards silencing anyone who still think of Snowflake as being simply a ‘database company’

Also check: Mark's Snowflake Summit - CrossFit beefs up its business users with a toned approach to data and Snowflake Summit - Snowflake embraces generative AI to help customers create new value from data.

A few more vendor picks, without the quotables:

Jon's grab bag - Cath raises hard questions in Pride Month - why LGBTQIA+ tech workers still need more than just a poster on the wall once a year - but they are the right questions. Derek assesses another milestone data policy in EU reaches agreement on Data Act - new rules for industrial data use forthcoming. Finally, Barb revisits the thorny-but-essential problem of attribution in Dealtale improves attribution, brings revenue science to marketers - but what about the 'dark funnel'?

Best of the enterprise web

Waiter suggesting a bottle of wine to a customer

My top seven

Overworked businessman


Hmmm... Doesn't it feel like the whiffs have already started? I'm not 100 percent sure this is a whiff: Google Says It'll Scrape Everything You Post Online for AI. It's basically the most inevitable news story of 2023. How about this: if you're surprised, that's a whiff. Also: shouldn't this put Google in the terms-of-service-change hall of shameless data-grubbery fame?

This isn't a whiff either, more like an anti-whiff from the  modern American heroes file:

Finally, I handed out some letter grades to vendors for the spring event season. There were a few nice grades, but also, alas, a couple of Fs:

Well, we have the summer to regroup at least - 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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