It’s no secret that IBM is trying to crack the ultimate code, so to speak, of generative AI – making it both safer to use and even more transformative, frankly, for people everywhere.
I recall a keynote presentation delivered by Kate Soule, IBM Program Director for Generative AI Research, at this past February’s ITEXPO 2024 in Fort Lauderdale, Florida. There, Soule explained in great detail how, in her words, “IBM is, and will continue to be, deeply committed to maintaining fairness and trustworthiness in the AI world.” (For additional IBM-centric stories, fellow GenAI Today writer and editor Greg Tavarez recently covered everything from IBM’s AI integrations for fans of golf’s iconic Masters, to IBM’s partnership with SAP with an objective of harnessing new GenAI capabilities for critical, industry-specific use cases in retail, utilities, manufacturing and more.)
Anywho, back to IBM’s commitment to fair AI. (Can’t spell “fair” without “ai,” after all… That pun will surely land somewhere, eh readers?)
Take, to cite but one example, IBM’s watsonx.governance. By tapping into it, business leaders can direct, manage and monitor their organizations’ AI projects by integrating IBM’s responsibility-first AI workflows for generative AI and machine learning across entire operations.
To cite another, take any of IBM’s Principles for Trust and Transparency that serve as guiding values behind their approach to AI ethics. These pillars state that:
- The purpose of AI is to augment human intelligence and benefit the many, not just the elite few.
- Data and insights belong to their creator, and IBM believes that data policies should be equitable and consistently reinforced, with a priority on openness.
- Technology must be transparent and explainable; organizations must be clear about who trains their AI systems, what data was used in training, and what went into the recommendations of their algorithms.
Explainability. Robustness. Privacy. It’s pretty clear how IBM is overseeing that words like these are molded into real-world action.
But what is actually being actioned by orgs’ CEOs right now? What’s the temperature, in a manner of speaking, of the overall “AI cultural shift” conversation? How are workforces reacting to working alongside GenAI-powered services?
As it so happens, IBM conducted a survey covering these very topics; right around this time last month.
Here’s the long-story-short scoop on that:
IBM’s survey indicates that 64% of surveyed CEOs (hailing from more than 30 countries and 26 distinct industries, to boot) have stated that “succeeding with generative AI will depend more on people’s adoption of it – their levels of excitement and respective hesitancies therein – than the technology itself.” However, 61% also stated that they’re pushing their orgs “to adopt it more quickly than some may be comfortable with.” To us, that sounds like both a heads and tails kind of statement; succeeding depends on higher adoption rates (and more exposure to and testing of AI), but is pushing comfortabilities in adopting it the right path?
Matthew Candy, Global Managing Partner at IBM Consulting, said that “With the incredible enthusiasm around generative AI, CEOs want to move beyond the hype to deliver long-term business impact. Yet, without the right people and respectful culture in place, progress may be slow.”
On that point, we and Candy agree. Resistance shouldn’t necessarily be the path; as teams embed AI in their enterprise strategies, it’s critical that “executives build a strong cultural mindset that fosters adoption and leads people well through these changes,” Candy added.
Other IBM findings included how:
- 40% of CEOs plan to hire additional staff because of generative AI, which may be at least partially in efforts to debunk “AI replaces humans” types of topics
- That said, 35% of CEOs’ workforces may require further retraining and reskilling between now and 2027; that three-year projection is up from 6% just three years prior in 2021.
- Regarding organizational collaboration and overall adoption challenges, 81% of CEOs said – in very good news – that “inspiring their team with a common vision on generative AI produces better outcomes,” albeit many acknowledged how bridging the gap between initial adoption and forward-moving strategic decisioning presents hurdles, too.
IBM’s survey covers a lot more; short-term AI targets versus long-term organizational progress, other risk factors and more; read the full study here.
At this moment in time, though, one thing remains crystal clear:
CEOs understand that not everyone has boarded the AI hype train, as it were. Getting everyone comfortable on board in good time is the goal if you’re on a team that’s exploring generative AI even further, and setting realistic expectations is part of that.
As the phrase goes, “Time will tell.”
Edited by
Greg Tavarez
