Sponsored by

Hello {{first_name | AI enthusiast}},

Oracle drops new agentic AI into Fusion ERP, Microsoft Advertising lands Product Explorer for merchants, and Robert Wachter rewrites hospital playbooks with AI‑driven care models—while regulators and cybersecurity watchdogs scramble to keep pace. Healthcare, finance, and retail all shift in real time.

Scroll down to catch the signals that matter.

The Ultimate Guide for Usage-Based Pricing for SaaS and AI

Implementing usage-based pricing successfully requires more than just a pricing strategy. It requires financial and operational infrastructure capable of handling dynamic pricing models, real-time usage signals, and increasingly complex monetization approaches.

In this guide, you'll learn  ⤵

  • Strategic Advantages + Implementation Guidance

  • AI Use Cases for Usage-Based Pricing

  • Insights from SaaS & AI finance leaders on overcoming challenges and maximizing UBP.

🧠 Robert Wachter Maps AI-First Clinical Practice

In an in‑depth interview, Robert Wachter explains how AI‑driven triage, diagnostic support, and ambient documentation will reshape care delivery, training, and hospital economics. His discussion of A Giant Leap highlights both transformative gains in efficiency and new liability, bias, and safety risks that demand rigorous governance and clinician oversight.

Health leaders should treat AI as a new clinical infrastructure layer, not just another IT project.

HubSpot AEO

Picture this. A buyer opens ChatGPT and asks for a recommendation in your category. Your competitor's name comes up. Yours doesn't. And that buyer never makes it to your website.

That's happening right now in markets everywhere. And most teams don't know it's happening because it never shows up in their analytics.

HubSpot AEO shows you exactly where your brand stands in AI search, where competitors are getting recommended instead of you, and tells you specifically what to fix. No expertise needed.

Try it free for 28 days. Just $50 a month after.

⚖️ Duane Morris Frames Corporate AI Compliance Playbook

Law firm Duane Morris introduces a multipart governance framework helping companies operationalize AI policies from board level through engineering and procurement. Their guidance on AI compliance breaks complex, fast‑changing regulations into structured phases, emphasizing inventorying models, monitoring vendors, documenting risk assessments, and aligning technical controls with legal accountability.

Expect investors and regulators to increasingly judge AI programs by whether this kind of structured framework exists.

📊 New AI Co-Pilots Target Financial Advisers’ Workflows

PlanAdviser spotlights a wave of advisor‑focused AI tools, from analytics agents that surface portfolio risk patterns to conversational platforms that auto‑draft responses to client queries. The reported launches in AI product and service offerings promise to offload routine service tasks, support personalization, and compress research cycles while raising new supervisory and disclosure expectations.

Firms that pair these tools with clear oversight rules will gain both productivity and compliance advantages.

🛡️ IIF Flags Frontier AI as Emerging Systemic Cyber Risk

The Institute of International Finance releases a staff paper on how frontier models could amplify cyberattacks, exploitation of zero‑day vulnerabilities, and cross‑border contagion in financial infrastructure. The IIF analysis of frontier AI and cybersecurity urges scenario planning, red‑teaming, sector‑wide exercises, and joint public‑private defenses to contain systemic risk.

Regulators and banks will increasingly treat AI security failures as macro‑prudential, not just IT, problems.

Half your market is one app away.

Your business is already on Instagram, SMS, and web chat. But 52 million immigrants in the US rely on WhatsApp to connect with businesses they trust — not email, not phone calls.

Wati helps you show up on WhatsApp and every channel they use. Are you still not there?

💼 BRG Scales AI & Decision Intelligence for Structured Finance

Berkeley Research Group expands its AI and decision intelligence practice with Jason Gu, focusing on securitization and structured credit. The announcement in The Secured Lender details how BRG’s expanded practice will apply machine learning to collateral analysis, stress testing, and deal structuring for lenders and investors.

Expect AI‑driven analytics to become standard in complex credit decisions and transaction advisory.

🚑 TeleDirect MD Quantifies Medical AI Hallucination Risks

TeleDirect MD publishes a technical review of hallucination rates in diagnostic and triage models, linking fabricated outputs to misdiagnosis, delayed care, and documentation errors. Their analysis of medical AI hallucination rates stresses robust prompt design, human‑in‑the‑loop validation, and clear patient communication to mitigate safety and liability exposures.

Health systems deploying generative tools must treat hallucination management as a core patient‑safety function.

🧩 Pew Trusts Weighs AI’s Double-Edged Role in Mental Health

Pew Trusts examines how chatbots, monitoring tools, and recommendation engines are entering therapy, crisis support, and screening workflows. The article on AI in mental healthcare details access and personalization benefits alongside serious concerns around bias, informed consent, data misuse, and escalation failures during acute crises.

Mental health providers will need new ethics frameworks before AI becomes a default front door to care.

🧾 Oracle Brings Agentic AI into Core Finance Operations

Oracle showcases four agentic AI capabilities in its Fusion ERP suite, including assistants for anomaly detection, cash optimization, automated close activities, and policy‑aligned approvals. The agentic AI update for Fusion ERP positions embedded agents as always‑on copilots that learn from historical transactions and organizational rules.

CFOs now have a playbook to shift finance teams from reconciliation work to higher‑value decision support.

🩺 AI Supercharges Healthcare Revenue Cycle Management

Health IT Answers outlines how predictive denials management, automated coding support, and intelligent work queues are transforming revenue capture. Its feature on AI’s role in medical billing highlights improved clean‑claim rates, faster reimbursements, and reduced manual follow‑up, while warning that poor data quality can amplify existing billing errors.

Hospitals harnessing AI in billing can unlock crucial margin relief without adding frontline clinical headcount.

🛍️ Microsoft Advertising Launches AI Product Explorer for Retailers

Microsoft Advertising introduces an AI‑powered Product Explorer inside Merchant Center, helping retailers analyze product catalogs, pricing, and competitive signals. The Product Explorer announcement details capabilities for grouping similar items, surfacing gaps, and optimizing feeds to boost ad performance and merchandising strategy.

Retail teams that master these insights can quickly reallocate budget toward high‑velocity products and profitable niches.


What trends are you tracking? Reply with your take or forward it to a colleague shaping AI strategy.

Share your unique referral link

Keep Reading