Enterprise Leaders Prioritize Secure-by-Design AI and Application Security

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Enterprise Leaders Prioritize Secure-by-Design AI and Application Security
Photo: Wired
tech· A press review of 3 outlets
  1. Security is also a top priority. Building resilient AI systems requires security to be embedded by design. The Accenture research shows that while early wins with AI agents are needed to build organizational confidence, it is systemic AI that will determine long-term success and overall business value.

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    MIT Technology Review

    In this environment, there is no tolerance for error, including the hallucinations that plagued early AI efforts. Agentic AI systems depend on rapid access to high-quality, well-governed data that is secure and accessible. In financial services, that data spans transactions, customer interactions, risk signals, policies, and historical context. The task of preparing that data for AI should not be underestimated. “Natural language is way more messy than structured data, and that makes the process of organizing and cleaning it up that much more important and also that much harder,” says Mayzak.

    Wired

    For most companies, AI has become a core part of their business offering. In that case, they have to understand the risks. They have to understand where models are running. They can't continue to use models where they don’t even know the location of the data centers, or the grid they're connected to. They have to know what the supply chain emissions are, transportation emissions, all these different things.

  2. As Mayzak says, “There are many different ways to describe how to execute a trade at a bank. In an agent-powered world, we need those descriptions to be deterministic—to give the same results every time. Yet we’re building on powerful but non-deterministic models. That’s incredibly tricky, but not impossible.”

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    ZDNet

    Avoid areas filled with edge cases, ambiguity, or constantly shifting rules. Those situations are far harder for agents to handle reliably and are more likely to create problems than deliver value.

  3. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

  4. How Pokémon Go is giving delivery robots an inch-perfect view of the world Exclusive: Niantic's AI spinout is training a new world model using 30 billion images of urban landmarks crowdsourced from players.

  5. Beyond the cleanup job: Redefining application security for the modern enterprise

  6. Secure-by-design is no longer just a developer concern. Enterprise leaders must treat application security as a board-level responsibility, with accountability, incentives, and customer risk reduction built in.

  7. Two terms are key to this approach: secure-at-the-source and secure-by-design. Both terms refer to the process of building security and reliability into code at the earliest stage of the software lifecycle. We'll focus on how security can be designed into all phases, from requirements and design through coding, dependency selection, build pipelines, deployment, and maintenance.

From the margins

3 details only one outlet reported

Independent claims that didn't surface elsewhere in our corpus. Treat as supplementary — not corroborated across outlets.

  1. 01 MIT Technology Review

    Financial services companies, therefore, require a trusted and centralized data store that is easy to access, dependable, and can be managed at scale.

  2. 02 Wired

    Building AI sustainably seems like a pipe dream as tech giants that previously made promises to cut emissions have been racing to build out massive data centers powered by fossil fuels.

  3. 03 ZDNet

    Find-and-fix security once made sense, but AI-assisted development, continuous deployment, and exploding vulnerability backlogs are changing the rules. The old application security playbook is breaking down fast.

Assembled from 7 corroborated claims drawn from 3 independent outlets. Every passage above is taken verbatim — Dorothy doesn't paraphrase or summarize.

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Coverage by Perspective

Enterprise
10
Academic
6
Culture
1

Source Similarity

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Sources (3)

  • wired
  • zdnet
  • mittech

Original Articles (17)

Academic Data readiness for agentic AI in financial services — MIT Technology Review
Academic Establishing AI and data sovereignty in the age of autonomous systems — MIT Technology Review
Culture What It Will Take to Make AI Sustainable — Wired
Academic World Models: 10 Things That Matter in AI Right Now — MIT Technology Review
Enterprise The patching treadmill: Why traditional application security is no longer enough — ZDNet
Enterprise Beyond the cleanup job: Redefining application security for the modern enterprise — ZDNet
Enterprise Stopping bugs before they ship: The shift to preventative security — ZDNet
Academic Implementing advanced AI technologies in finance — MIT Technology Review
Enterprise The future of IT service delivery is built on AI and automation — ZDNet
Enterprise How this travel company's AI rollout drove a 73% satisfaction boost: A 5-step playbook for your business — ZDNet
Enterprise Building an agentic AI strategy that pays off - without risking business failure — ZDNet
Enterprise Give your 'human-level agents' a proper head start with these 3 best practices — ZDNet
Enterprise The 5 myths of the agentic coding apocalypse — ZDNet
Academic Cyber-Insecurity in the AI Era — MIT Technology Review
Academic Operationalizing AI for Scale and Sovereignty — MIT Technology Review
Enterprise Moving from AI pilots to business-wide value requires a superhighway - how to ramp up — ZDNet
Enterprise Forget productivity: Here are 5 strategic shifts that drive real AI value — ZDNet