Forrester's latest report indicates that the AI hype wave is reaching its peak, with many enterprises expected to delay a significant portion of their AI spending until 2027 due to challenges in proving return on investment (ROI). As a response to increasing regulatory complexities, 60% of Fortune 100 companies are anticipated to appoint heads of AI governance by next year. This shift highlights a growing focus on compliance and risk management rather than pure innovation. Meanwhile, G2's findings present a contrasting narrative, revealing that nearly 60% of companies have successfully deployed AI agents, with a low failure rate and high satisfaction among users.

Despite the positive deployment statistics from G2, a study by Atlassian uncovers a paradox: while individual usage of AI tools has surged, 96% of businesses report no significant improvements in efficiency or innovation. The survey indicates that only 3% of executives believe AI has driven transformational change within their organizations. This disconnect suggests that while AI tools are being adopted widely, their impact on actual business outcomes remains limited, leading to skepticism among decision-makers.

Anthropic's recent research raises concerns about the security of large language models, revealing that as few as 250 malicious documents could effectively poison these models, compromising their functionality. This alarming finding underscores the vulnerabilities present in AI systems, particularly those relying on public or partner data. The implications for businesses are significant, as they must now consider the security of their AI systems alongside their operational capabilities.

In the hardware arena, Apple and Intel are igniting a new chip race, with Apple launching its M5 chip, which boasts enhanced AI performance and graphics capabilities. Intel's Panther Lake chip is set to compete with improved efficiency and performance metrics. As AI technology becomes increasingly integrated into devices, managed service providers (MSPs) must adapt to the complexities of endpoint management and AI readiness. The evolving landscape emphasizes the need for governance, security, and effective measurement of AI outcomes, positioning MSPs as crucial enablers in this transition.

Four things to know today

00:00 Forrester, G2, Atlassian, and Anthropic Paint a Complex AI Picture — Success, Stagnation, and Security Risk

06:09 Apple’s M5 and Intel’s Panther Lake Show the Future: Every Device Becomes an AI Engine

09:17 GoTo, Gradient, and LevelBlue Show the Next MSP Evolution — Refinement, Not Reinvention

12:21 Microsoft’s Final Windows 10 Update and IE Mode Lockdown Signal the End of Legacy Tolerance

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