#ai-adoption

#ai-adoption

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.

"Our report shows that AI adoption is outpacing governance. It's a clear gap - 93% of organizations are using AI but only 7% have fully embedded governance frameworks."

AI Overviews in Google Search now has 2 billion monthly users, increasing from 1.5 billion in May 2025, reflecting strong consumer demand for AI features.

Microsoft announced it would start evaluating employees on their usage of AI tools like Copilot, indicating that AI fluency is now essential for job performance.

Analysts have raised Nvidia's price target to $250 per share, indicating a potential market cap of $6 trillion, amidst a significant wave of AI adoption.

"Today, usage is dominated by these generalist AI systems, such as OpenAI's ChatGPT or Google's Gemini, but we're seeing, starting with specific categories, this move into more specialized apps."

"AI's impact on the labor market remains limited and there is no sign of a significant impact on most labor market outcomes."

The most profound changes are happening at the infrastructure level - in how banks are building platforms designed for continuous evolution rather than periodic overhaul.

AI adoption remains notably slow despite the perception of widespread use, with only 8% of enterprises achieving organization-wide adoption and less than 20% reporting revenue increases.

Nearly two-thirds of B2B revenue leaders in the UK and Europe report first year ROI from AI adoption, with 19% achieving it within three months.

There is a complete reset in how data is managed and flows around the enterprise. If people want to seize the AI imperative, they have to redo their data platforms in a very big way. And this is where I believe you're seeing all these data acquisitions, because this is the foundation to have a sound AI strategy.

Many businesses have the availability to begin adoption and testing. For other use cases like healthcare, it's not complete or finished in a wrapped-up way businesses can adopt.