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AI isn’t just something to adopt; it’s already embedded in the systems we rely on. From threat detection and response to predictive analytics and automation, AI is actively reshaping how we defend against evolving cyber threats in real time. It’s not just a sales tactic (for some); it’s an operational necessity.
Yet, as with many game-changing technologies, the reality on the ground is more complex. The cybersecurity industry is once again grappling with a familiar disconnect: bold promises about efficiency and transformation that don’t always reflect the day-to-day experiences of those on the front lines. According to recent research, 71% of executives report that AI has significantly improved productivity, but only 22% of frontline analysts, the very people who use these tools, say the same.
When solutions are introduced without a clear understanding of the challenges practitioners face, the result isn’t transformation, it’s friction. Bridging that gap between strategic vision and operational reality is essential if AI is to deliver on its promise and drive meaningful, lasting impact in cybersecurity.
Executives love AIAccording to Deloitte, 25% of companies are expected to have launched AI agents by the end of 2025, with that number projected to rise to 50% shortly thereafter. The growing interest in AI tools is driven not only by their potential but also by the tangible results they are already beginning to deliver
For executives, the stakes are rising. As more companies begin releasing AI-enabled products and services, the pressure to keep pace is intensifying. Organizations that can’t demonstrate AI capabilities, whether in their customer experience, cybersecurity response, or product features, risk being perceived as laggards, out-innovated by faster, more adaptive competitors. Across industries, we're seeing clear signals: AI is becoming table stakes, and customers and partners increasingly expect smarter, faster, and more adaptive solutions.
This competitive urgency is reshaping boardroom conversations. Executives are no longer asking whether they should integrate AI, but how quickly and effectively they can do so, without compromising trust, governance, or business continuity. The pressure isn’t just to adopt AI internally to drive efficiency, but to productize it in ways that enhance market differentiation and long-term customer value.
But the scramble to implement AI is doing more than reshaping strategy, it’s unlocking entirely new forms of innovation. Business leaders are recognizing that AI agents can do more than just streamline functions; they can help companies bring entirely new capabilities to market. From automating complex customer interactions to powering intelligent digital products and services, AI is quickly moving from a behind-the-scenes tool to a front-line differentiator. And for executives willing to lead with bold, well-governed AI strategies, the payoff isn’t just efficiency, it’s market relevance.
Analysts distrust AIIf anyone wants to make their job easier, it’s a SOC analyst, so their skepticism of AI comes from experience, not cynicism. The stakes in cybersecurity are high, and trust is earned, especially when systems that are designed to protect critical assets are involved. Research shows that only 10% of analysts currently trust AI to operate fully autonomously. This skepticism isn’t about rejecting innovation, it’s about ensuring that AI can meet the high standards required for real-time threat detection and response.
That said, while full autonomy is not yet on the table, analysts are beginning to see tangible results that are gradually building trust. For example, 56% of security teams report that AI has already boosted productivity by streamlining tasks, automating routine processes, and speeding up response times. These tools are increasingly trusted for well-defined tasks, giving analysts more time to focus on higher-priority, complex threats.
This incremental trust is key. While 56% of security professionals express confidence in AI for threat detection, they still hesitate to let it manage security autonomously. As AI tools continue to prove their ability to process vast amounts of data and provide actionable insights, initial skepticism is giving way to more measured, conditional trust.
Looking aheadClosing the perception gap between executive enthusiasm and analyst skepticism is critical for business growth. Executives must create an environment where analysts feel empowered to use AI to enhance their expertise without compromising security standards. Without this, the organization risks falling into the hype cycle, where AI is overpromised but underdelivered.
In cybersecurity, where the margin for error is razor-thin, collaboration between AI systems and human analysts is critical. As these tools mature and demonstrate real-world impact, trust will grow, especially when their use is grounded in transparency, explainability, and accountability.
When AI is thoughtfully integrated and aligned with practitioner needs, it becomes a reliable asset that not only strengthens defenses but also drives long-term resilience and value across the organization.
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- A reputable source claims the first public iOS 26 beta will land on or around July 23
- That would be later in the year than usual
- There's already an iOS 26 developer beta
It’s now over a month since iOS 26 was announced, and although it’s available in developer beta, the public beta is yet to launch. But we do now have a good idea of when the first public beta might land.
According to Apple watcher Mark Gurman in a reply to a post on X by @ParkerOrtolani, the first iOS 26 public beta will probably land on or around July 23.
That’s a bit unusual, as typically we’d have had the first public beta before then. For example, the first public beta of iOS 18 launched on July 15 last year, following its announcement on June 10. So this year, with iOS 26 having been unveiled on June 9, we’d if anything have expected to already have the first public beta.
around the 23rdJuly 15, 2025
A worthwhile waitStill, if Gurman is right there’s not too much longer to wait, and it should be worth the wait too, as iOS 26 is a significant upgrade for Apple’s smartphone operating system.
It includes a completely new look, with more rounded and transparent elements, plus redesigned phone and camera apps, a new Apple Games app, and more.
Of course, we’d take the claim of it landing on or around July 23 with a pinch of salt, especially with that being later than normal. But Gurman has a superb track record for Apple information, and either way we’d expect it to land soon.
If you can’t wait a little big longer though, you can always grab the developer beta – the next version of which may well even land before July 23. To get that, check out how to install the iOS 26 developer beta.
You might also like- Claude for Financial Services launches specifically for the financial industry
- Users can access powerful Claude 4 models and other Claude AI tools
- The system integrates with internal and external data sources
Anthropic has launched a special edition of Claude designed for the highly regulated financial industry, with a focus on market research, due diligence, and investment decision-making.
The OpenAI rival hope for financial institutions to use its tool for financial modelling, trading system modernisation, risk modeling, and compliance automation, with pre-built MCP connectors offering seamless access to entperise and market data platforms.
The company boasted that Claude for Financial Services offers a unified interface, combining Claude's AI powers with internal and external financial data sources from the likes of Databricks and Snowflake.
Claude for Financial Services is here to take on the financial sectorAnthropic highlighted four of the tool's key benefits: powerful Claude 4 models that outperform other frontier models, access to Claude Code and Claude for Enterprise, pre-built MCP connectors, and expert support for onboarding and training.
Testing revealed that Claude Opus 4 passed five of the seven Financial Modeling World Cup competition levels, scoring 83% accuracy on complex excel tasks.
"Access your critical data sources with direct hyperlinks to source materials for instant verification, all in one platform with expanded capacity for demanding financial workloads," the company shared in a post.
Anthropic also stressed that users' data is not used for training its generative models in the name of intellectual property and client information confidentiality.
Besides Snowflake for data and Databricks for analytics, Claude for Financial Services also connects with the likes of Box for document management and S&P Global for market and valuation data, among others.
Among the early adopters is the Commonwealth Bank of Australia, whose CTO Rodrigo Castillo praised Claude for its "advanced capabilities" and "commitment to safety." The Australian banking giant envisions using Claude for Financial Services for fraud prevention and customer service enhancement.
You might also like- Financial leaders still rely on regular tools like Excel for automation tasks over AI
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