AGENTIC INTELLIGENCE Newsletter #26

Welcome to Agentic Intelligence—the first newsletter dedicated to AI agents and made by them! Behind each edition is a digital newsroom of seven expert agents scanning the world, with my human insights layered on top.

Together, we explore how Agentic AI is reshaping work, business, and life.

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Here are the Top five Agent Breakthroughs of the Week that you can't miss:

1️⃣ UiPath’s Agentic AI Pivot: Why the Market Is Underestimating PATH’s Platform Play

UiPath is repositioning from robotic process automation (RPA) into an enterprise agentic AI platform, leveraging partnerships with Nvidia, Snowflake, Google Cloud and OpenAI and launching orchestration tools like Maestro to deepen infrastructure integration.

Key Takeaways:

• UiPath is repositioning from robotic process automation (RPA) to an enterprise 'agentic AI' platform, aiming to expand its total addressable market by embedding autonomous agents across workflows and customer infrastructure.

• UiPath reported fiscal Q2 revenue growth of 14.4%, which beat Wall Street estimates, and management highlighted robust ARR momentum and customer net retention (NRR), indicating increased platform stickiness among enterprise clients.

• The analyst rates UiPath a buy based on a combination of attractive valuation, accelerating growth and strategic positioning, while explicitly noting near-term execution and transition risks as the company shifts from RPA to an agentic AI platform.

My Take:

This shift at UiPath is exactly the kind of platform inflection I track in my consulting work: a vendor moving from point automation to orchestrated, persistent agentic services that can sit inside enterprise stacks. In my analysis, the combination of 14.4% Q2 revenue growth, strong ARR and NRR commentary, and partnerships with Nvidia, Snowflake, Google Cloud and OpenAI creates a credible pathway to deeper infrastructure embedding. I've been highlighting the importance of multi-agent orchestration and persistent memory features in enterprise adoption, and UiPath's Maestro and partner strategy map cleanly onto those requirements.

2️⃣ Salesforce Bets Agentforce 360 as the Enterprise 'AI Agent' Hub

Salesforce acquired process-mining vendor Apromore and is integrating process intelligence with agentic AI to create Agentforce 360, aiming to provide end-to-end visibility and autonomous actions across sales, service, and operations.

Key Takeaways:

• The strategy pairs process-aware insights with AI agents that can surface next-best actions and reduce manual work, positioning Agentforce 360 as a foundation for enterprise agents rather than just a point AI feature.

• Salesforce revised pricing across products including Slack and introduced Flex Credits for Agentforce to give customers flexible, pooled AI capacity, which is designed to ease pilots and scaling but requires buyers to map credits to usage patterns.

• Competitors include hyperscalers embedding AI-native CRM, vertical AI vendors with domain-specific agents, and open-source modular stacks; the core competitive question is who delivers more effective, cheaper, and easier-to-integrate agents.

My Take:

This is a deliberate platform play: Salesforce is marrying process mining with agentic AI to make Agentforce 360 the operational layer for autonomous workflows. In my consulting work I see customers demand both visibility and actionability — Apromore gives Salesforce the telemetry side while Agentforce targets execution. My analysis is that flexibility in consumption models matters as much as capability, so the Flex Credits move is sensible but creates a new buyer calculus. I’ve been highlighting that agentic AI could represent a multi-trillion-dollar opportunity (some estimates cite a $10 trillion addressable space) if it reaches scale, and I’m tracking in my research that 85% of enterprise AI efforts stall without clear cost-to-value mapping.

⭐⭐⭐ How to Succeed in Your Agentic AI Transformation

I’ve teamed up with Cassie Kozyrkov (ex-Google Chief Decision Scientist) and Brian Evergreen (author of Autonomous Transformation) to launch a first-of-its-kind course: Agentic Artificial Intelligence for Leaders—built for decision-makers, not coders. This course delivers the strategy, models, and hard-won lessons you need to lead in this new era—directly from those who’ve built and implemented agentic systems at scale.

What you'll learn

✅ How agentic AI differs from traditional automation and generative AI

✅ Where it's already working—real-world implementations across industries

✅ Strategic frameworks to start and scale agentic AI today

✅ Lessons from leaders who’ve already deployed these systems at the enterprise level

My take

While generative AI caught everyone’s attention, AI agents are quietly redefining how work gets done—faster, more autonomously, and with far greater impact. Leaders who understand this shift will unlock new value. Those who don’t may get left behind. Join us for the First Executive Masterclass on Agentic AI Strategy and Implementation ⭐⭐⭐

3️⃣ n8n Hits $2.5B Valuation After $180M Series C — The Automation Layer Betting on Agentic AI

n8n, a Germany-based startup that helps companies develop and deploy agentic AI automations, raised $180 million in a Series C that values the company at $2.5 billion and included participation from Nvidia’s investment arm and lead investor Accel.

Key Takeaways:

• Accel states that more than 80% of workflows built on n8n now embed AI agents, showing the platform mixes agentic AI, deterministic steps, and human inputs to automate and orchestrate business processes.

• CEO Jan Oberhauser said revenues increased tenfold over the past year and pointed to customer cost savings at firms such as Vodafone, while he declined to disclose exact revenue figures, leaving some growth details unspecified.

• PYMNTS Intelligence research cited in the article finds 26.7% of CFOs now plan to raise generative AI budgets in the next 12 months versus 53.3% a year ago, indicating a shift from experimental spending to more disciplined deployment.

My Take:

This funding milestone for n8n is not just another unicorn round — it reflects a deeper shift toward agentic orchestration as a distinct enterprise layer. In my consulting work I see teams struggle to combine persistent memory, multi-agent orchestration and deterministic business logic; n8n’s claim that 80% of workflows embed agents aligns with the need for a composable orchestration fabric. My analysis shows vendors that solve integration, observability and safe human-in-the-loop coordination will win early enterprise adoption.

4️⃣ CFOs Quietly Give Agents the Keys — 7% Already Live, 5% Piloting

Nearly 7% of U.S. enterprise CFOs have deployed agentic AI in live finance workflows and another 5% are running pilots, per PYMNTS Intelligence’s September 2025 CAIO Report. CFOs are putting agents on low-risk, catchable-error tasks while keeping treasury, statutory compliance, and payment authorization offline until guardrails and explainability mature.

Key Takeaways:

• CFOs are assigning agents to low-risk tasks where errors are detectable and reversible, such as drafting planning documents and monitoring expense anomalies, while avoiding high-stakes areas like treasury and payment authorization pending stronger controls.

• Organizational culture, demand for transparency, and control frameworks are driving adoption decisions more than raw technical capability, with firms preferring repetitive, rules-driven, and analytically intensive functions for early durable use.

• The transition is expected to proceed in stages: automation-ready finance functions will see earlier, lasting adoption while higher-risk activities wait for robust guardrails, explainability, and auditability before moving to agentic workflows.

My Take:

This CAIO Report is a clear signal that finance is entering the agentic AI era faster than many expect, but the move is surgical and risk-aware rather than wholesale. In my consulting work I see CFOs gravitating to agentic systems to relieve reporting burdens and cost pressure, which matches the report’s finding that ~7% are live and ~5% are piloting. My analysis shows that readiness hinges on governance and explainability as much as model capability.

5️⃣ Silent Leaks: How Chatty AI Agents Turn Your Trade Secrets Into Open Secrets

Agentic AI and multi-agent workflows default to oversharing unless engineering, policy, and contractual controls are enforced across memories, credentials, and inter-agent messaging. Companies must adopt memory classification, per-task short-lived keys, content screening, policy-as-code, cryptographic message labels, canary markers, and strict vendor contracts to prevent IP leakage and meet regulatory disclosure timelines.

Key Takeaways:

• Agents often persist snippets as 'memories' that increase exfiltration risk; the article recommends segregating stored data into distinct buckets (restricted, confidential, general) aligned with a company’s classification system, enforcing separate access rules and retention policies to prevent unauthorized flow between buckets.

• Least-privilege, short-lived credentials should be issued per task so planning agents only see labels and execution agents open approved file versions; keys must auto-expire at task end to limit credential reuse and lateral data access by agentic workflows.

• Contracts with AI vendors must reflect operational reality, specifying no training on customer data, minimal telemetry, prompt prompt/response deletion, strict subprocessor controls, and IP/confidentiality terms, while incident playbooks must align with regulators such as the SEC and NYDFS.

My Take:

Agentic AI is not just a privacy problem; it’s an operational and IP governance crisis that will reshape enterprise security and vendor strategy. In my consulting work I see teams that treat agents as features rather than distributed systems with persistence, identity, and messaging—my analysis is that this mismatch creates predictable leakage. I’ve been highlighting the need for memory classification, per-task ephemeral keys, and policy-as-code as foundational defenses, and I’m tracking in my research how contracts and telemetry must change to match these controls.

What would you add to this conversation? Did we miss any important news this week? Your voice matters—let’s build the future together.

If you found this valuable, share it with your network. Because very soon, we won’t say, “There’s an app for that.” We’ll say, “There’s an agent for that.”

See you next week,

—Pascal

Crafted by seven AI agents and shaped by Nicolas Cravino, this newsletter is a true human–AI collaboration, with layout support from Pascaline Therias.

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