Artificial intelligence (AI) may be sexy to talk about, but many businesses are not adopting coherent strategies around their use of it to truly harness its efficiency potential. Does its deployment sometimes add to workloads, but fail to add to profits, because of this incoherence?

Some studies seem to indicate yes to all of these queries, pointing to how companies often underestimate the complexity involved, devaluing the fundamental organizational shift needed. Let’s look at a few of them.

AI compliance use strategy

Only 22% of organizations have a visible, defined AI strategy despite clear evidence that strategic AI adoption drives significantly better outcomes, according to new research from Thomson Reuters.

Organizations with AI strategies are twice as likely as those with informal adoption approaches to experience revenue growth from AI, and 3.5 times more likely to achieve critical AI benefits compared to those with no significant adoption plan, the report said.

The survey of 2,275 global professionals across legal, risk, compliance, tax, accounting, audit, and global trade found that more than half of organizations are already seeing return on investment from AI adoption, with improved efficiency and productivity being the most common benefits. But 40% of organizations are adopting AI without a strategy, and 30% of professionals say their organizations are moving too slowly on AI implementation.

More findings from that report include:

• 80% of professionals believe AI will have a high or transformational impact on their profession over the next five years, but only 38% expect significant change at their own organization this year.
• 55% of professionals have experienced or expect significant changes in their work, with 46% reporting skills gaps on their teams, mainly in technology and data competencies.
• 88% of professionals favor having profession-specific AI assistants.

The survey showed that organizations with a mature AI framework had deployed AI tools across multiple governance, risk, and compliance functions, with those organizations using AI to track risk proactively, using AI specifically for such things as predictive risk modeling, shaping risk posture and strategic planning rather than for simple check-the-box compliance items.

In terms of tracking regulatory change, 60% of the organizations deemed to be maturely using the tools use AI-powered automation for regulatory change monitoring, compared to 56% at mid-tier and 48% at lower-maturity organizations.

Roadblocks in organizations

Deploying AI in a way that incentivizes acceptance, learning and adoption is important, as one analysis showed that over half (51%) of the professionals surveyed felt like learning AI was another job.

LinkedIn’s global research showed that, on its site, there has been an 82% increase in people posting about feeling overwhelmed and navigating the pace of AI change this year. Adding to that concern, the mounting pressure to upskill in AI is fueling insecurity among professionals at work LinkedIn’s research showed a third (33%) admitted they feel embarrassed by how little they understand it, and 35% said they feel nervous talking about AI at work for fear of sounding uninformed.

For younger professionals, that fear of not being sufficiently skilled in using AI is most acute, with Gen Z professionals admitting they exaggerate or lie about their AI skills at work, as compared to Gen X.

If only a minority of employees know how to use these AI tools to work smarter and faster, the business using them is not benefiting, the provider is not going to do well over the long term, and investors of both enterprises are likely to get nervous.

Speaking of nervous investors: Meta’s stock fell last month on reports the company is looking at downsizing its AI division. Meta’s aggressive hiring strategy caught headlines for a while, but the sudden hiring pause fueled some concerns that investments in AI are moving too rapidly. OpenAI CEO Sam Altman told a group of journalists recently he believes AI is in a bubble.

Companies that bought AI tools from trusted providers were far more successful in harnessing their potential than those that built internal pilots, according to the MIT study.

But many investors and analysts take this information to mean that Meta is just digesting what it has absorbed recently in its spending spree and that (overall) tech stocks are still undervalued.

Another way to incentivize adoption of the tools could be to speak less about AI replacing jobs, although this is hard to promise. Does a business avoid speaking about its overall plans with AI adoption, speak of it in terms of replacing jobs, or refer to the potential to improve work-life quality? This communication strategy is an important one to get right.

Salesforce CEO Marc Benioff has voiced the idea that humans and AI bots will soon work side by side, as have other tech executives. But a Pew Research Center survey shows that 32% of Americans think AI will lead to fewer job opportunities.

AI and ROI

Recently, MIT researchers studied 300 public AI initiatives with the objective of trying to learn the reality of AI’s impact on business. Their findings included:

• 95% of organizations found zero return despite enterprise investment of $30 billion into GenAI.
• Even firms that are using AI right now are not seeing widespread disruption.

Important to note is that companies that bought AI tools from trusted providers were far more successful in harnessing their potential than those that built internal pilots, according to the MIT study.

Some of the most successful use cases of AI depended on companies improving their AI usage over time by adopting best practices and training their employees, and this might mean selecting the right AI tech provider who can offer the right tools and training, both.

As noted in Axios: “Big tech capital expenditure has not been this high since the year 2000. We all know what happened after that. Will this time be different?”