Core Intelligence
When Governance Enables Speed
As artificial intelligence matures, many organizations are discovering that the biggest obstacle to scale isn’t capability—it’s confidence. In a preview of Newsweek’s upcoming AI webinar, “AI Governance: Balancing Innovation and Risk,” Suraj Srinivasan, a professor at Harvard Business School and the webinar’s host, framed the current slowdown as a rational response to unresolved risk rather than a failure of ambition.
“Organizations are quite rightfully concerned about risk and safety—privacy, customer harm, mistakes,” Srinivasan said. “But that means they can’t get the most value from what the technology is capable of doing.”
That tension helps explain why so many AI initiatives remain confined to narrow pilots. The technology is powerful, but the systems needed to oversee it—clear accountability, escalation paths and shared risk frameworks—are still catching up. Without those guardrails, leaders default to caution, even when the upside is obvious.
Srinivasan’s most useful reframing is that governance is not a brake on innovation, but the condition that makes acceleration possible. “The engine is powerful,” he said, “but we are deliberately unable to use the maximum potential…because we are still behind in figuring out the risk, safety and governance aspects of it.” His analogy was blunt: “If you can’t create good brakes, you can’t put in powerful engines.”
That idea sits at the center of the broader conversation shaping the webinar. J. Trevor Hughes, CEO and president of IAPP, emphasized that trust and safety are not trade-offs against innovation, but the enablers that allow new technologies to move into real-world use. From the enterprise risk perspective, Manny Padilla, board president of the Risk and Insurance Management Society and vice president of risk management and insurance at MacAndrews & Forbes, stressed the importance of clear internal policies that define how AI can be deployed before systems move into production. And Justin McCarthy, chief executive of the Professional Risk Managers’ International Association, pointed to a broader shift underway: AI is not necessarily eliminating the role of risk professionals, but rather reshaping what effective risk management looks like.
The implication for leaders is structural. AI maturity will not be defined by who experiments first, but by who builds the institutional muscle to manage uncertainty at scale. Companies that treat governance as an afterthought are likely to keep AI boxed into low-risk use cases. Those that invest early in oversight, ownership and clarity position themselves to unlock far more of the technology’s value.
As Srinivasan put it, the point of good governance isn’t restraint—it’s control. “The idea of the brakes is not to go slow,” he said. “It’s to help you steer—and actually go fast.”
You can read the full article here: “What’s Holding AI Back? Join Newsweek’s AI Governance Webinar.” And you can learn more about the webinar below.
Upcoming Webinar
AI Governance: Balancing Innovation and Risk
Join Prof. Suraj Srinivasan of the Harvard Business School and Keith Enright, partner at Gibson Dunn, co-chair of both the firm’s Tech and Innovation Industry Group and the Artificial Intelligence Practice Group, and the former chief privacy officer at Google, for an essential webinar exploring the high-stakes intersection of AI innovation and risk.
The live webinar, “AI Governance: Balancing Innovation and Risk,” will take place on Tuesday, February 24, at 1 p.m. Eastern.
Register, for free, right now.
Prompt Injection
What’s one recent insight you’ve learned about AI?
“For years, customization has been taboo in venture-backed software. It’s the enemy of scale, marred by one-offs, heavy services, and margin compression. Investors would sooner fund a lemonade stand because the ‘build once and sell many times’ model is the path to profitability.
Healthcare never fit the mold, as each hospital system is different. Be it their objectives, workflows, populations, or operating constraints, customization was unavoidable. Tech companies slowly morphed into consulting firms, and the laid-back dress code gave way to suits.
My ‘ah-ha’ realization is that AI changes the math—and that customization and scale are no longer trade-offs.
As a core capability, AI addresses the barriers that block scale. Valuable healthcare data has been buried in fragmented systems, such as digital records, claims, and cost structures. The insights were there, but making data work together—and be transactable—required a massive human effort. AI changed that.
AI ingests and standardizes datasets and can map to a health system’s workflows when software goes live. And the months-long implementation cycle is gone. Instead, solutions are tailored to a system’s goals, whether that’s improving how patients find the right doctor or cutting wait times, without having to rebuild from scratch.”
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.
Register now.
Run Log
AI use case of the week
By Adam Mills
For Bonutti Technologies, the challenge wasn’t proving that UV-C works. The science behind ultraviolet disinfection is well established. The harder problem was execution: applying UV-C correctly, safely and consistently across real-world clinical environments, where room size, layout and time pressure can undermine even proven protocols.
Dr. Peter Bonutti, who leads the company, said the gap between laboratory efficacy and day-to-day use became increasingly clear. “The problem was ensuring that level of disinfection performance could be achieved reliably, every time,” he said. When UV-C is applied correctly, it can reduce targeted pathogens by up to 99.9 percent, but manual processes vary, environments differ and protocols are often compressed.
To close that gap, Bonutti Technologies built AI directly into its UVCeed system to manage both safety and dosage. Using integrated cameras and sensors, the system evaluates spatial and operational factors in real time, adjusting UV-C delivery based on the specific environment rather than relying on fixed settings. AI also acts as a safety layer: If a person or animal enters the treatment area, the system automatically shuts off and resumes only when the space is clear.
The result has been greater confidence and repeatability. Treatment times have been optimized, and facilities have gained a more standardized disinfection process aligned with high pathogen-reduction targets. Instead of relying on assumptions, staff can trust that each cycle is completed correctly, with clearer documentation and fewer variables left to chance.
For Bonutti, the experience has reinforced a broader lesson about AI in clinical settings. “Achieving high disinfection efficacy isn’t just about the technology itself—it’s about execution,” he said.
When AI is used to reduce variability and reinforce proven science like UV-C, rather than replace clinical judgment, it becomes a practical tool for delivering consistency, safety and trust at scale.
Have an AI use case to share with us? Email us at: [email protected]
Context Window
■ Super Bowl advertisers made AI a blockbuster marketing theme, from Svedka’s largely AI-generated big-game spot to a very public sparring between Anthropic and OpenAI over how AI ads will shape public perception and the future of AI marketing. [Newsweek]
■ Databricks’ CEO says AI won’t kill SaaS but will make many traditional software categories “irrelevant,” as the company hits a $5.4 billion revenue run rate with major growth coming from its AI products. [TechCrunch]
■ Thomson Reuters says it has acquired Noetica, an AI-native platform for corporate transaction intelligence, and plans to integrate its analytics and structured market intelligence capabilities across CoCounsel for deal workflows like benchmarking terms and drafting support. [Thomson Reuters]
■ Cisco is rolling out major enhancements to its AI Defense and Secure Access Service Edge (SASE) offerings, adding AI-driven traffic inspection and runtime protections designed to safeguard agent-oriented workflows and enterprise infrastructure against evolving threats. [Cisco Newsroom]
■ A CIO analysis finds spending on AI infrastructure and data centers is set to drive global IT budgets in 2026, with AI and data technologies growing far faster than other categories and putting pressure on traditional IT services spend. [CIO]
Transfer Protocol
Tracking executive moves across the AI landscape
Vincent S. Capone, who most recently served as chief financial officer and general counsel at Spectral AI, Inc., has been appointed chief executive officer of the company, where he will lead commercialization efforts as Spectral AI advances its AI-driven DeepView burn wound assessment system toward broader clinical and market deployment.
David T. Scott, a longtime technology executive with leadership experience at AWS, Twitter and AT&T, has been named interim chief executive officer of VERSES AI Inc., where he will focus on converting the company’s research and development into commercial products, strengthening go-to-market execution and driving near-term revenue growth while a permanent CEO search is underway.
Logan Thompson, an executive with nearly two decades of strategic finance leadership experience across SaaS and technology companies, has been appointed chief financial officer at Klear.ai, where he will support the company’s growth as it expands its AI-powered solutions for underwriting, risk, claims and insurance analytics.
Jeremy Forman, formerly vice president of global R&D AI, data and analytics at Pfizer, has been promoted to chief AI, data and analytics officer at the company, where he will oversee enterprise-wide integration of artificial intelligence, data science and analytics across research, development and business functions.
Thomas Roderick, PhD, an AI practitioner with experience deploying production-scale AI systems across utilities, health care and federal agencies, has been named chief AI officer at Global Clean Energy, Inc., where he will co-lead the company’s newly formed AI Division focused on developing AI solutions for clean energy optimization, resilience and climate-related challenges.
Magic Moment
What’s the most fun or unexpected way you’ve used AI lately?
“The most unexpected and rewarding way we’ve used AI is in modeling real-world motorcycle riding behavior to help prevent incidents before they happen. By combining radar, cloud analytics and mobile and vehicle systems, we’re able to identify patterns in how riders respond to traffic, obstacles and everyday riding conditions.
What stood out to me is how much context matters. AI isn’t just about collecting data—it’s about understanding when, where and why that data exists. We learned quickly that rider safety is a holistic challenge. It requires understanding behavior, surroundings and decision-making as one connected system.
The result is a more proactive safety platform that helps riders recognize risk earlier and respond faster. It’s not about reacting after something goes wrong—it’s about giving riders the right insights in the moment.”