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Cyber AI Chronicle
By Simon Ganiere · 15th December 2024
Welcome back!
Project Overwatch is a cutting-edge newsletter at the intersection of cybersecurity, AI, technology, and resilience, designed to navigate the complexities of our rapidly evolving digital landscape. It delivers insightful analysis and actionable intelligence, empowering you to stay ahead in a world where staying informed is not just an option, but a necessity.
Table of Contents
What I learned this week
TL;DR
Businesses are shifting from selling tools and services to guaranteeing measurable outcomes through "Results as a Service" (RaaS) or "Outcome as a Service" (OaaS). This model reduces complexity and risk for customers by delivering specific results rather than just capabilities. AI, particularly through adaptive AI agents, plays a pivotal role by automating tasks, analyzing data, and ensuring consistent outcomes at scale. » READ MORE
It took me 6-8 hours to get a working iOS application to track stock/crypto trade using Cursor AI. I did write on AI programming assistant before, but this is really mind-blowing. I have zero experience in iOS programming and throughout the whole thing I have not typed a single line of code. Is it the best application either? Probably not. Is the code super high quality…can’t really judge but I’m sure an experience iOS dev would find a lot to improve…but in the end this is just a very good illustration of my point of last week: be curious and try to adopt those new tool…or someone else will 😉
OpenAI pulled a great marketing move with their “12 days of OpenAI” basically staying in the news continuously for more than 2 weeks…brilliant strategy! So this week we got:
Google released the Gemini 2.0 Flash model as well. The model is twice as fast and more powerful than 1.5 Pro with improved multimodal, text, code, video, spatial understanding and reasoning performance on key benchmark. » MORE
Results as a Service—How AI is Transforming the Value Proposition
In today’s rapidly evolving business landscape, organizations are moving away from traditional models that simply sell products or standardized services. Instead, there is a growing shift toward delivering outcomes—or what many term “Results as a Service” (RaaS) or “Outcome as a Service” (OaaS). Where once clients might have paid for a piece of software or a fixed-duration service engagement, they’re now demanding guaranteed, measurable results. This approach is changing the game for both providers and consumers of technology-enabled services, and nowhere is this more visible than in the integration of Artificial Intelligence (AI), particularly advanced AI agents, into these frameworks.
From Products and Services to Outcomes: Why This Matters
Traditional business models often center on transactions: a company sells a product or a service, and once that transaction is complete, the provider’s responsibility effectively ends at delivery. In contrast, an OaaS model flips this dynamic. Instead of providing just a tool or a raw capability, the provider commits to delivering a specific, quantifiable business result. This might be an agreed-upon increase in sales conversions, a guaranteed reduction in manual processing time, or an assured improvement in operational resilience.
The value proposition for customers is clear: reduced complexity, minimized risk, and clearer ROI. Organizations no longer have to piece together various tools, hire specialized talent, or navigate a learning curve just to achieve an outcome. They pay directly for that outcome. For providers, while this model introduces higher accountability, it also allows them to differentiate and cement long-term relationships.
AI’s Role in Delivering Outcomes at Scale
Enabling OaaS at scale would have been a tall order even a few years ago. Delivering guaranteed results in dynamic, rapidly changing environments can be immensely complex. This is where AI steps in, providing the necessary intelligence and adaptability to ensure consistent outcomes, even as conditions shift.
For instance, consider AI-driven agents that not only process data in real-time but also learn and adapt from it. These agents can continuously monitor performance indicators, identify emerging risks, and self-adjust tactics without waiting for human intervention. By leveraging machine learning models, these agents optimize the path to the desired outcome, reduce operational overhead, and quickly respond to market or internal changes.
RaaS will rise, because people want results, not
software.
AI Agents—The Brains Behind the Scenes
At the heart of OaaS models fueled by AI are so-called AI “agents.” These dynamic entities integrate with data streams, enterprise systems, and external APIs—constantly refining their strategies. They automate routine tasks, analyze vast data sets, and even predict outcomes based on historical patterns. Their ability to operate autonomously enables businesses to deliver on outcome-based promises without extensive human intervention.
Real-World Examples of OaaS in Action
Here are some examples of how businesses are leveraging OaaS with AI to drive measurable results:
Customer Service Desk: Zendesk has introduced outcome-based pricing models for its AI-powered customer service agents. Customers only pay for issues resolved autonomously by AI, ensuring alignment between costs and tangible results. This approach automates up to 80% of customer interactions, reducing operational costs while improving efficiency and satisfaction
Mezink is delivering guaranteed influencer marketing outcomes to brands, leveraging AI across steps - discovery, evaluation, activation and reporting - leading to 3x-10x better ROAS.
Customer Engagement and Sales Conversion: Firms like Agent.ai promise a boost in lead conversions. AI agents analyze customer interactions, tweak messaging strategies, and continuously optimize outreach.
IT Infrastructure Resilience: Providers like ScienceLogic ensure compliance with performance and availability metrics, using AI to monitor system health and prevent disruptions.
Bringing It All Together
The rise of OaaS models represents a shift in how value is defined and delivered. It’s not just about having a shiny new technology or a vast array of capabilities on paper; it’s about tangible, measurable outcomes that align directly with the customer’s business goals. AI makes this possible at scale and complexity levels previously unthinkable.
As more organizations embrace these outcome-based models, expect to see them partnered closely with cutting-edge AI capabilities. Both parties—provider and customer—win: the provider differentiates itself in a competitive market, and the customer gets exactly what they want: a result, not just a tool. In this new landscape, AI isn’t just an enabler; it’s the key ingredient that makes Results as a Service not only feasible but transformative.
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Worth a full read
Defeating Adversary-in-the-Middle phishing attacks
Key Takeaway
Implementing multifactor authentication is crucial for stopping most password-related attacks.
Passkeys and phishing-resistant credentials offer strong security against Adversary-in-the-Middle attacks.
Conditional Access policies and managed devices create significant hurdles for adversaries.
Anomaly detection and risk-based policies help mitigate potential phishing threats.
URL-specific, device-specific, and user-specific passkeys are difficult for attackers to exploit.
Cryptographic methods in phishing-resistant credentials prevent attackers from intercepting authentication processes.
Passkeys require direct user interaction, enhancing security with biometric or PIN authentication.
Phishing-resistant credentials are essential in meeting cybersecurity regulations and standards.
Broad adoption of passkeys strengthens security by applying public-private key cryptography.
How CISOs Are Spending Their New Budgets
Key Takeaway
Cybersecurity budgets are fluctuating, leading to diverse strategic priorities for CISOs.
Identity management, particularly nonhuman identities, is crucial for enterprise security.
Generative AI presents significant security challenges, necessitating innovative solutions.
Data Loss Prevention is resurging due to AI's impact on data classification.
Application security is evolving towards holistic posture management and runtime response.
The sprawl of cloud, SaaS, and identity ecosystems demands comprehensive security strategies.
Cybersecurity vendors have vast opportunities for innovation in diverse problem spaces.
Consolidation within ecosystems helps CISOs manage security more effectively.
The security of the software supply chain is increasingly prioritized by CISOs.
Holistic security strategies are replacing traditional point solutions for better protection.
Wisdom of the week
We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.
Contact
Let me know if you have any feedback or any topics you want me to cover. You can ping me on LinkedIn or on Twitter/X. I’ll do my best to reply promptly!
Thanks! see you next week! Simon