#ai-adoption

#ai-adoption

For the first time this summer, it's now soft skills. It's human skills; it's things like problem solving, judgement, creativity, taste.

Markets got a shock in late August from an unlikely place: a survey by MIT finding that 95% of generative AI pilots at large companies were failing. That prompted a tech sell-off and talk of whether AI was forming into a stock-market bubble. And another piece of the puzzle just fell into view: the Census Bureau finds that AI adoption rates are starting to decline among major firms.

The report found the best-performing companies are driving better outcomes with a more transparent structure, smarter systems and practical uses of AI. They align on specific outcomes, shared metrics, and consistent operating rhythms- not just strategy slides or campaign goals. Rather than launching disconnected pilots, the report found leading companies use embedded, role-based AI to guide content usage, improve coaching and act in real time.

While the general trend is upwards, there's been a decline in the use of AI for companies with more than 250 employees. That cohort is the group most likely to use AI, according to the bureau, peaking just shy of 14% and falling back down to 12% over summer surveys. While this represents a small - and perhaps temporary - decline, it does suggest some degree of hesitation on the part of large enterprises, some of which are growing frustrated at poor returns on investment.

AI is already replacing my job without firing me (for now). Legal executives expect the work of in-house legal teams to start and end with AI tools. This expectation makes sense given that a key role of legal executives is to use legal costs efficiently, and AI tools have the most appealing potential to reduce time and costs on research, contract drafting, case management, providing guidance, and other projects.

But AI isn't just another disruption: it's a moment of reinvention. If your company is investing in AI but seeing uneven results, it may not just be a technology problem. While technology may still be evolving in some areas, a challenge also lies in adoption. In many organizations, that breakdown happens along the lines of hierarchy, trust, and communication, not just code or capability. This is HR's opportunity to lead the transformation.

Agencies buying a higher-tier bundle of ServiceNow's information technology products will see discounts as high as 70% though September 2028, the US General Services Administration said Wednesday in a statement. The deal follows a spate of similar announcements touting big discounts on software and cloud products used by federal workers, as the GSA has sought to centralize negotiations with technology vendors to leverage the federal government's purchasing power.

As businesses like yours turn to AI to drive innovation, data has become the strategic lever for agility and growth. Yet for many organizations, the promise of AI remains out of reach because entrenched legacy data systems stand in the way of progress. These aging architectures, characterized by siloed data, technical debt, and a lack of scalability, create significant roadblocks that inhibit innovation and increase costs.

Companies are investing heavily in AI, in spite of the fact that they aren't yet seeing a big return. A recent report from MIT found that 95% of organizations that have adopted AI haven't seen any return on the investment at all. (However, the 5% of companies who are seeing the return are "extracting millions in value," according to the report.)

Sure, AI makes a convenient cover for business executives who were already looking to downsize or outsource their labor force, but the tech's myriad hallucination issues, legal risks, and security baggage make it ill-suited to automate human jobs. That's to say nothing of the fact that 95 percent of businesses gunning for an AI overhaul see their efforts end in failure.

The State of Embedded Software Quality and Safety 2025 from Black Duck reveals a disconnect between the organizational use of AI and AI security. The embedded software landscape is transforming, largely driven by AI, with 89.3% of organizations already utilizing AI coding assistants and 96.1% integrating products with open source AI models. However, 21.1% of organizations still lack confidence in their capabilities to prevent AI from opening the door to vulnerabilities.

Researchers at Microsoft say AI is having a net positive effect on software development, with the technology "augmenting developers rather than replacing them". The claim follows the publication of a examining the use of the technology amidst rising concerns over its impact on the workforce. The use of AI in software development has become a source of "intense debate" in recent months, researchers noted, with some industry stakeholders suggesting it will ultimately replace developers and reduce entry-level opportunities.

The short answer, according to Morgan Stanley's report, is that corporate adoption of AI has the capacity to reshape the future of work, saving businesses nearly $1 trillion a year. The report, "AI Adoption and the Future of Work," which was viewed by Fast Company, suggests S&P 500 companies could accrue annual net benefits totaling some $920 billion a year. The bank looked at potential future states of AI-driven labor impacts, and saw benefits from cost reduction and a productivity lift.

Every company wants to have an AI strategy: A bold vision to do more with less. But there's a growing problem-one that few executives want to say out loud. AI initiatives aren't delivering the returns they were hoping for. In fact, many leaders now say they haven't seen meaningful returns at all. IBM recently found that only 1 in 4 AI projects hit the expected ROI. And BCG's research goes further still: 75% of businesses have seen no tangible value from their AI investments.

The deals were part of GSA's OneGov strategy, in which the government streamlines the acquisition of services by operating as one entity; that way individual federal agencies don't have to negotiate their own separate deals.

When it comes to AI, you'd be hard-pressed to find a more groveling cheerleader than the humble CEO. As hype around the software grows, business execs have become astonishingly comfortable sharing their hopes that AI will soon make human labor a thing of the past. Now, even as Wall Street begins to reckon with the empty promises of AI automation, one CEO is bragging about laying off almost all of his workforce in the face of the tech - a move he says he would make again.

Why can't every engineer just onboard by the end of the week?

It's still predominantly, 'Are you hitting your sales numbers?'

This observation is data-backed by recent research by McKinsey, which finds that Millennials, followed by Gen Z, are set to drive AI adoption across organizations because they're the most confident in using AI tools. Up to 90% of people in both groups report feeling comfortable using generative AI at work. That's because these young professionals are innately attuned to the tech's paradigms in their personal lives.

Corporate America is on the brink of a radical transformation as artificial intelligence adoption could unlock nearly $1 trillion a year in savings, according to a sweeping new analysis by Morgan Stanley. The bank calculates 90% of jobs will be touched in some way by AI automation or augmentation, with cost savings flowing directly from reduced headcount, natural attrition, and automation of knowledge-intensive but routine tasks.

Building trust means being intentional in how AI is used and keeping people at the center of every decision, according to Kathy Pham, vice president of AI at Workday.

Over the last few years, there has been a clear transformation in how CFOs perceive AI technology. Initially exhibiting caution, now they are increasingly viewing it as a primary driver for efficiency and profitability.

Most employees don't see how AI applies to their daily tasks. The benefits sound promising, but without a clear link to their responsibilities, it's hard to see the point.

Leaders are spending millions on AI tools, but their investment focus isn't going to succeed. They think it's a technology problem when it's really a human and technology problem.

When considering AI adoption, it's important to recognize that the success of these technologies relies heavily on the human expertise guiding them, not just on the technology itself.

Twelve months after rolling out a state-of-the-art AI coding assistant, only 41% of engineers had tried it. Female engineers adopted at just 31%, while those 40 and older adopted at 39%.

The 'competence penalty' leads to AI users being perceived as less competent by peers, impacting their willingness to adopt AI tools, especially among women in technical roles.

Design teams mainly use AI for generating copy, documentation, and content, which accounts for 75.2 percent collectively, helping unblock individual contributors to focus on design.