Summary Bullets:

• Concerns about missing the AI boat have many corporate executives pushing AI application development mandates.

• However, research indicates that far too few organizations are realizing the kind of expected dividends in terms of cost savings, revenue generation, productivity gains, and innovation. What can they do differently to make the most of their investments?

To say artificial intelligence (AI) has become ubiquitous is almost an understatement. Just under 90% of all enterprises today use AI to support at least one corporate function, according to consulting firm McKinsey and Company, with 56% of all organizations applying the technology across three or more discrete tasks. This pace of adoption is unprecedented. Stanford University’s 2026 AI Index Report says 53% of the global population had been using generative AI (GenAI) within three years of widespread availability. For comparison’s sake, it was 12 years before the personal computer reached 40% of the population.

The appeal is obvious: Executives see AI’s promise as an engine to accelerate cost savings and operational efficiencies while delivering data-driven analytics that produce better outcomes and rapid revenue expansion. On paper, the technology is a game-changer, the kind that has corporations pressing lines of business to quickly develop and deploy AI-driven applications to realize fast returns. But the reality, particularly given the nascent nature of the technology and the relatively limited experience of most organizations in developing and deploying it, presents a much more complicated reality.

Figures like the 95% AI project failure rate quoted by the Massachusetts Institute of Technology (MIT) in the research university’s 2025 study of 300 public AI implementations accounting for a $30 billion to $40 billion total investment raise widespread concerns about poor outcomes and an imminent AI bubble implosion. Broader studies show that while less drastic, early AI results have delivered less than stellar results. IBM Institute for Business Value (IBV) research reports that the 1,250 IT executives surveyed in mid-2026 had seen a return on their AI investment of 17%. The result: Nearly two-thirds of all AI projects fell short of corporate goals. Separate IBM research points to internal technical oversight and management issues often beyond IT’s control, which can cut into 20% of AI returns. These issues range from disjointed processes, erratic measurement, limited visibility, and high upfront costs.

The source of much of this friction is trying to apply AI project budgets across multiple departments where priorities and end goals may be wildly different. The simple guidance for enterprises, particularly those with limited AI experience and even lower success rates, is to allocate resources to smaller, more focused AI projects initially. The goals should closely align with the unit’s requirements, and should by their nature, be easier to monitor and measure and need fewer resources. Enterprises can leverage learnings from these individual engagements over time, which they can then scale for larger inter-departmental projects.

As with any cutting-edge technology investment, failures are bound to happen more frequently than any organizations want to see. The key is to strike the right balance of adequate resource allocation and manageable implementations with clearly established governance over monitoring, management, and overarching objectives.

The post Under Pressure to Demonstrate AI ROI, Too Often Organizations Come Up Short appeared first on IT Connection.

Summary Bullets:

• In August, Meta admitted liability regarding social media’s addictive qualities on children, reaching a $17.1 billion settlement with US states and the District of Columbia.

• While seen as a victory by critics, the settlement is insufficient to introduce the sweeping changes needed to have a measurable effect.

Just weeks after Meta, the parent company of social media giants Instagram and Facebook, promised to restrict access to some of the more controversial features of its platform to settle a multi-billion dollar lawsuit, California Governor Gavin Newsom signed a bill tightening social media controls for children. The California law, which goes into effect in 2028, mandates social media accounts for users under age 16 be private, limits algorithmic feeds for minors, masks children’s location data, and turns off overnight notifications for underage users. Unlike similar legislation passed by other states like Illinois, the California law allows parents to amend social media restrictions. Newsom also signed a bill that requires AI companies to reveal to minors whether they are communicating with a non-human entity. The legislation also prevents children from accessing risky content on subjects like self-harm.

The California law and the Meta settlement come at a time when governments across the US and around the world are imposing regulations on social media and AI companies. The goal is to protect minors from damaging content and addictive online platform characteristics that interfere with the mental health of minors. Governments ranging from Australia and Indonesia to the EU have enacted restrictions barring children and young teenagers from unlimited content access. In the US, government social media regulatory and legal activity is occurring at the state and local levels.

Social media platforms have been under fire for years as parents and researchers voice concerns about hazardous effects of social media on younger users. Research from both public and private sector entities finds that social media use can have wide-ranging repercussions on children’s mental health and brain development. Advisories from the US Surgeon General and the American Psychological Association also cite negative physical and social consequences to minors from sites like Instagram and Snapchat, including sleep deprivation and exposure to content promoting eating disorders.

While social media companies reject accusations that their platforms propagate addictive usage patterns, successful litigation and settlements favoring plaintiffs such as the August Meta resolution show they are on the defensive. As part of the resolution of that settlement, Meta agreed to set a two-hour daily platform limit for users under 18 on Facebook and Instagram. The company will also block overnight access to the online sites and eliminate some features such as ‘like’ counts that have negative effects on users’ mental health. Meta will pay roughly $12 billion initially to the states, with the remaining $5 billion disbursement dependent on TikTok, Google (YouTube’s parent), and Snap (SnapChat’s parent) also settling and agreeing to pay financial penalties and make similar feature access changes.

On paper, experts critical of the effects of social media use on children and teenagers welcome the feature changes. But while large-scale settlements and platform adaptations show at least implied admission of responsibility by platform vendors, it is not necessarily an indicator of future feature development plans or end user behavior. Regulatory restrictions imposed by governments such as Australia have had limited impact on user access as teenagers find ways to navigate around controls.

The post Despite Meta’s $17.1 Billion Lawsuit Settlement, Questions Linger About Reducing Negative Social Media Effects for Children appeared first on IT Connection.

Summary Bullets:

• As rapid advances in AI application development drive demand for more processing capacity, US-based cloud providers are investing heavily in building out facilities to support these deployments.
• But not everyone is on board with expansion plans, with public criticism stalling some development efforts, forcing hyperscalers to pivot to new locations, often in more remote areas.

AI is changing the cloud landscape, creating the near-term need for a vast increase in processing power and storage space. Hyperscalers are responding with substantial facility construction plans. Just this year alone, Amazon Web Services, Google, and Microsoft Azure are pouring a total of $500 to $700 billion into extensions of their data center footprints. Given AI’s dominance in enterprise technology investment plans, this is a logical track. However, not everyone is on board with these aggressive development plans -and AI plays a role in that resistance.

Fifty-two percent of adults are more worried than excited about AI, according to results from a Pew Research Center survey of 3,488 adults fielded earlier this year. Those queried had trepidations related to AI about everything from job displacement and interference with human creativity to unreliable or even malicious output.

AI anxiety is translating into opposition to in-region data center expansion. A Gallup poll of 1,000 US adults conducted earlier this year, found that 71% of those surveyed are totally opposed to the building of new data center facilities used to support AI applications in their region. By comparison, 53% object to construction of a new nuclear energy plant – a perennially unpopular build in the US for decades.

Participants in the telephone survey cited several concerns related to the new data center expansion, primarily focused on resource consumption, cost, and quality-of-life impacts. Fifty percent said excessive resource requirements associated with these builds in areas like water and energy consumption along with secondary effects such as loss of farmland, wildlife, and deforestation are behind their resistance to facilities’ expansion in their areas. Twenty-two cited concerns about property values and increased traffic. Another 20 percent noted that new data centers might bring higher utility costs and cost of living expenses.

Localities are hearing and responding to this resistance to data center expansion. Due to regional complaints, more than $100 billion in facility buildouts was stopped or disrupted in just one quarter. Over 550 local governments have suspended new facility construction or stopped issuing new permits.

Industry observers warn that impeding expansion could have unintended harmful consequences, including hindering the establishment of effective cyber defenses against hostile adversaries and creating barriers to the development and deployment of technological innovations. But cloud providers have been adept at circumventing obstacles to expansion, finding locations in more remote areas that are more hospitable to new facility construction.

Hyperscalers and other cloud providers are targeting more rural areas in the South and Midwest, and more remote locales in states like Oklahoma, Maine, and Virginia. Nearly half of all new data center builds are in the south, with states like Texas being hot spots.

The post Public Opposition to New Data Centers Disrupts but Doesn’t Derail US Facilities’ Expansion appeared first on IT Connection.