By Adam Mills
AI Editor
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Editor's note: This is AI Impact, Newsweek's weekly newsletter where each week, we will explore how business leaders are unlocking real value through artificial intelligence.
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Core Intelligence
Why AI Governance Is Struggling to Keep Up
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Across many organizations, the pace of AI adoption is outstripping the systems meant to govern it. As companies push to deploy new tools, a familiar tension is emerging: the technology rewards speed, while governance frameworks are built to slow things down.
“There is this perception, rightly or wrongly, that making the right bets on AI is existential,” said Keith Enright, partner and co-chair of the Technology Innovation Group at Gibson Dunn and former global chief privacy officer at Google. In that environment, he added, “speed is a survival imperative.”
That pressure can put governance structures under strain. Compliance reviews, risk assessments and legal approvals were built for earlier generations of enterprise software, when development cycles unfolded over months or years. AI systems can move far faster, allowing new capabilities to be tested and deployed before oversight processes fully catch up.
Suraj Srinivasan, professor at Harvard Business School, framed the problem through a simple analogy during a recent Newsweek AI Agenda webinar: “The faster the car, the better the brakes that you need.”
In theory, governance should function as those brakes—allowing companies to move quickly while still maintaining control. In practice, many organizations are still trying to determine how oversight should work when AI systems are capable of generating insights, decisions and automation at scale.
The challenge extends beyond technical risk. Paul McDonagh-Smith, senior lecturer at the MIT Sloan School of Management, said governance is increasingly about institutional design: how companies distribute authority, responsibility and accountability as AI tools spread across the enterprise. The question is not simply whether AI works, but who ultimately owns the decisions it influences.
Philip Brittan, CEO of enterprise intelligence platform Bloomfire, pointed to a related concern. As AI capabilities expand across departments, organizations risk creating fragmented systems of oversight, where different teams deploy tools under different assumptions about risk, accountability and control.
Taken together, those pressures point to a broader shift. AI adoption is no longer just a technical upgrade—it is forcing organizations to rethink how governance itself operates. The task is not only to manage risk, but to design oversight structures capable of operating at the same pace as the technology they are meant to control.
For companies experimenting with AI today, that may be the central governance lesson. Speed can unlock enormous value, but without clear ownership and consistent oversight, it can also create blind spots that grow as quickly as the technology itself.
You can watch the discussion and read the full article here: Companies Are Racing Into AI. Oversight Isn’t Keeping Up.
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AI Impact Awards & Summit
The Newsweek AI Impact Awards seek to identify and recognize uniquely innovative AI solutions that solve critical business problems in different industry segments, or significantly advance capabilities. Recognition comes not from ideas, but from measurable IMPACT on business operations.
Prompt Injection
What’s one recent insight you’ve learned about AI?
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"For small businesses, the clock is always ticking. While large enterprises can run longer experimentation cycles with AI, SMBs, especially in fast, high-stakes industries like legal and accounting, cannot. Our new Legal Industry Report shows that while 54 percent of legal professionals are optimistic about AI's long-term impact, around two-thirds say concerns about solution cost and maturity are slowing firm-wide adoption. Optimism is high, but for businesses that simply don't have the time, budget, or client patience for tools that add noise without results, scrutiny is higher.
A good rule of thumb is if an AI solution isn't producing measurable outcomes within 30 days, it's more distraction than meaningful innovation. While the technology itself may be unique, the key differentiator is how it's embedded into the systems and workflows that already power the business. When deployed in day-to-day operations and measured against real outcomes, AI strengthens agility, decision-making, and financial confidence - all of which are critical to the long-term health of SMBs."
Have your own lesson to share? Email us at: ai.newsletter@newsweek.com
Run Log
AI use case of the week
By Adam Mills
In clinical trials, the data arrives long before the answers do. Studies generate enormous streams of information—from patient outcomes to operational metrics—but extracting new insights can still take time.
At Lindus Health, a technology-driven clinical research organization, sponsors running trials could monitor live dashboards, yet deeper analysis often required days of back-and-forth between teams to produce new queries or visualizations.
To close that gap, Lindus Health embedded AI agents directly inside its clinical trial platform. Sponsors can now describe the data they want to explore in plain language. The agent generates the query, builds the visualization and returns a validated answer within the secure environment where the data already resides. What once involved extended email exchanges and manual analysis can now be completed in seconds.
That speed changes how studies are managed. According to the company, sponsors gain continuous visibility into trial performance, emerging risks and operational bottlenecks. The faster access to insight strengthens oversight of patient safety, supports quicker decision-making and helps keep studies on schedule.
The experience also highlighted a critical requirement for trust and validation.
“Integrating LLMs into existing enterprise platforms unlocks real value only when strong safeguards are in place,” said Meri Beckwith, co-founder and co-CEO of Lindus Health. “It is critical that any insights surfaced are based on hard data.”
To support that standard, each deployment includes encryption, secure access controls, detailed audit logs and validation processes aligned with regulatory expectations.
With those protections in place, the company says AI can move from a peripheral analytical tool to a system embedded directly in the operational flow of clinical research—delivering faster answers while maintaining trust in the data.
Have an AI use case to share with us? Email us at: ai.newsletter@newsweek.com
Context Window
■ As companies race through the AI hype cycle, workplace data suggests women may receive less encouragement and support to adopt AI tools—raising concerns that uneven access to training could widen existing leadership and opportunity gaps if companies fail to deploy AI inclusively. [Newsweek]
■ Security researchers have identified vulnerabilities in a fast-growing open-source AI agent platform that could enable prompt-injection attacks to extract sensitive data, highlighting cybersecurity risks as enterprises begin deploying autonomous agents inside internal systems. [The Hacker News]
■ Researchers warn that increasingly autonomous AI agents may pose risks similar to insider threats inside corporate networks, potentially collaborating to bypass safeguards or exfiltrate data if organizations deploy them without strong governance controls. [The Guardian]
■ Developers are beginning to isolate AI agents inside containerized environments to limit access to sensitive systems, reflecting a growing push to build stronger security guardrails as enterprise adoption of agentic AI accelerates. [Forbes]
■ Surging electricity demand from AI-driven data centers is forcing U.S. utilities to plan massive upgrades to the electric grid, raising questions about who will pay for the infrastructure needed to support the next wave of AI computing. [The Wall Street Journal]
■ European lawmakers have reached a preliminary political agreement on updates to the AI Act, including changes to timelines and oversight provisions, underscoring how regulators are still working through implementation details as compliance approaches. [IAPP]
■ Lucid plans to roll out an in-vehicle AI assistant and expand autonomy partnerships, part of a broader push to build new software-driven revenue streams alongside its vehicle lineup. [Newsweek]
Transfer Protocol
Tracking executive moves across the AI landscape
Dhiraj Sankala, formerly chief technology officer at Sift Healthcare and previously vice president of data intelligence at Zelis, has been appointed chief AI and technology officer at Intellivo, where he will lead the continued advancement of the company’s technology platform for third-party liability identification with a focus on greater speed, accuracy and scale.
Simon Elcham, Trustpair’s co-founder and former chief technology officer, has been appointed chief AI officer at the company, where he will lead its cross-functional AI strategy, AI risk management framework and companywide adoption efforts as Trustpair formalizes its AI governance model.
Maureen Tomlinson, who will continue alongside her position as senior vice president of operations for Markel in Canada, has been appointed head of AI at Markel International, where she will shape the division’s approach to AI, support senior leaders in identifying strategic opportunities and drive the delivery and adoption of AI solutions through its new AI Centre of Enablement.
David McLaren, most recently a leader of data and enterprise automation at Coca-Cola Canada Bottling, has been appointed enterprise data & AI leader at GHD, where he will lead the development of the firm’s Enterprise Data Platform and foundational AI capabilities as part of its IS & Technology leadership team.
Dr. Ali Alkhafaji, most recently chief AI and technology officer at Omnicom Precision Marketing and previously global CEO and president of TA Digital, has been appointed chief executive officer at Apply Digital, where he has been tasked with deepening the company’s AI leadership and building what the company describes as an AI-integrated services firm of the future.
Magic Moment
What’s the most fun or unexpected way you’ve used AI lately?
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“I recorded a sales call with a facility owner and ran it through AI afterward, mostly just to see what it would pick up. It basically told me I was selling my product wrong. I spent most of the call walking through features and tech specs, and AI pointed out that the moment the buyer actually got engaged was when we talked about the experience their players would have. I'd been so deep in the product that I couldn't see it. AI caught it in seconds.
I'd been on a bunch of these calls and thought they were going well. Turns out I was leading with the wrong thing every time. Now I don't pitch the scoreboard, I pitch what it does for the facility. That shift came from one call recording and five minutes with AI. It changed how I sell, how I write ads, how I talk about the product on my website. I didn't expect AI to make me better at the human side of running a business, but honestly that's where it's had the biggest impact.”
Experience some AI magic? Tell us about it at ai.newsletter@newsweek.com
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