Agentic AI—systems that act on data rather than just analyze it—is being hailed as a cure-all for the healthcare industry’s inefficiencies. Payers, providers, and pharma firms are investing fast. But how much of what’s being promised is actually feasible today, and how much is branding-driven hype?

In a new white paper, I explore the advertised, actual, and emerging uses of agentic AI in healthcare. From Salesforce’s acquisition of Informatica to UK-based “AI” firms exposed for running smoke-and-mirrors operations, it’s clear that the field needs clarity—and accountability.

This blog provides a preview of what you’ll find in that deeper dive.

​What’s Being Promised:

• Automated prior authorizations and appeals in payer operations
• Clinical documentation and decision support
• Ambient listening for providers
• AI agents in trial site selection and adverse event detection for pharma

What’s Working Now:

• Clinical ambient tools (Nuance DAX, Abridge, Suki) are helpful but still human-in-the-loop
• Automation of narrow workflows like intake triage or formulary lookups
• Some trial modeling, where data quality is strong and regulatory paths are clear

The Gap:

• APIs struggle with fragmented or unclean data
• Regulatory bodies still require auditability and explainability
• Firms overpromising agentic autonomy rarely disclose how brittle their models are

Consulting Firms: The Connective Tissue
It’s not just product companies shaping this space. Many consulting firms—Cognizant, Deloitte, EPAM, Accenture, Slalom, and others—play a unique hybrid role. They may:

• Build their own agentic tools (sometimes as ISVs)
• Partner with platform vendors like Salesforce or AWS
• Drive real-world implementation and integration of AI in healthcare settings

Far from adding confusion, these firms often bring much-needed structure, compliance rigor, and domain context. They’re helping AI move from lab demo to daily workflow.

Case in Point:

British “AI” firm Repliq was exposed by the Financial Times for passing off manual processes as generative AI, with junior developers writing responses behind the scenes. It was a textbook case of vaporware wrapped in buzzwords.

Read the White Paper:
The companion white paper explores:

• Why Informatica fills a critical data hygiene gap in Salesforce’s Data Cloud
• How to spot poser AI companies (regardless of whether they’re vendors or services firms)
• The regulatory drag on agentic deployment in clinical vs. administrative workflows
• Who’s actually building credible healthcare AI—and how to tell

Conclusion:
AI won’t save healthcare overnight. But real, responsible agentic AI—built on clean data, governed properly, and validated openly—can still move the needle. We just have to know where to look.

Read more: 
Get the Full White Paper - Agentic AI in Healthcare: Sorting Real Innovation from Vaporware

Finding a new job has never been easy. But in today’s environment — with AI systems controlling the first gates of opportunity — it feels more like running an obstacle course in the dark. I’ve been living this firsthand since late last November when I was part of a larger lay-off at my last company. I started what I thought would be a focused, determined job search. What I didn’t realize was just how much the rules had changed since the last time I had to do this.
​
This is a look at what I’ve learned — the frustrations, the pitfalls, and a few ways forward that might help others going through the same thing.​

The First Wall: AI as the New Screener
One of the biggest shifts in the job search is that AI filters almost everything now. Resumes aren’t first seen by a recruiter; they’re parsed by an Applicant Tracking System (ATS) or an AI matching tool. The goal of these systems is to “streamline” the flood of applicants. The side effect? Strong candidates may never even get a human glance.

I had to research this, but in this environment, the way a resume is written really matters — but not always in a way that reflects real capability. It’s about keyword optimization, matching the phrasing of the job description, and being “AI-readable.” Clear formatting, simple structures, and matching terminology can mean the difference between being seen and being screened out.

​It can be discouraging — I knew I could excel in a role, if only someone would talk to me.

The Volume Problem (and Horses with Horns)
I found that every job posting now gets hundreds — sometimes thousands — of applicants. LinkedIn is real good at telling us how many applicants applied before you. Companies know this, and it creates another strange behavior: setting “unicorn” requirements. Instead of listing what’s actually necessary for success, job descriptions become laundry lists of every ideal skill and education credential under the sun, no matter how unrealistic.

It’s easy to get caught in cycles of self-doubt (“Maybe I’m not enough”) when the truth is often: nobody is that good.

Hiring has become aspirational on their side — and demoralizing on ours.

Networking Still Works — But It May Not Suffice
​Networking remains one of the few consistent ways to bypass the AI filters. I had many former co-workers (thank you all!) helping me through this process. A warm introduction, a recommendation, or even a comment on someone’s LinkedIn post can open doors. But what happens when your network is tapped out, or simply doesn’t align with your goals?

This is where traditional advice falls short. “Just network more” isn’t useful if the people you know may be able to point you to a door, or even open it for you, but the goals of the business you are trying to enter just don't align with yours.

That being said, I found that reaching out to old colleagues works when it is not done in desperation, but with updates on what I was working toward  — and showing a real curiosity about what they are doing. It is also important to be consistent - reaching out frequently works.

Re-skilling: Not Just Courses — Realignment
A lot of noise is made about re-skilling — endless ads for courses, certifications, and bootcamps. I found that re-skilling is not just about stacking new badges onto your profile. It’s about realigning ones personal story to where the market is going.

There is hope here - this might mean reframing existing skills for adjacent industries, not starting over from scratch.

It might mean showing how your background applies to problems companies actually have right now — not problems they had the prior fiscal year.

Scam City
Another hard reality that I encountered: scam job sites and fake postings.

These scammers prey on people’s desperation, offering interviews that never happen, asking for personal information, or dangling fake remote jobs.

Some signs I’ve learned to look for:

• Companies no one has ever heard of and vague job descriptions
• No traceable recruiter or company presence online; if there is a referenced recruiter, they look like they just got set up on LinkedIn yesterday
• Requests for lots of personal information up front
• Personal email domains (like Gmail, Outlook, or AOL Mail)
• Immediate offers without interviews

If something feels off, it usually is. Legitimate job boards usually point you to an application directly at the company you are applying to, or they have an integrated application process like LinkedIn, Welcome to the Jungle, WellFound and others.

Thoughts on "Networking Platforms”
​In my early search, I tried out several job-hunting “networking” platforms — the ones that promise a supportive community, introductions, or direct access to hidden jobs.

My experience?

• Most people on these platforms were just like me: searching, not hiring.
• Conversations were polite but rarely useful to me. Everyone needed help, but few could offer it, moderators included.
• Some platforms charged fees to access “premium” roles — most of which were either reposts from public job boards or old listings. Cross-referencing these jobs on LinkedIn or company job boards showed many of these jobs already closed out.

As I was not meeting much success with these services, I tried to understand why. The broad consensus seems to be the same: networking sites for job seekers are often echo chambers, not actual pipelines to opportunities.

I treated my stay with the networking groups for what it is: emotional support, maybe an occasional tip — but not a main job search strategy.

Lessons Learned — and the Way Forward
After months in the trenches, here’s what I’d tell anyone starting or stuck in the process:

• Write resumes for the machines — but never lose the human story.
• Don’t take unicorn job descriptions personally. After some research and talking to peers, I found many companies don’t really expect to find them.
• Treat networking like building bridges, not hunting trophies. Small, real conversations seem to work.
• Networking platforms as a main strategy did not work for me. They may work for others, but I found the focus on real-world connections to be more effective.
• Skill alignment to real-world needs, not re-skilling for imaginary job descriptions.
• Protect your mental energy. I found that not every opportunity is real, and not every rejection is about me.
• Persistence is survival. Some days I felt invisible. Some days I felt like I was really close to my next job. I have to keep moving either way.

The rules have changed, but one thing hasn’t: people still hire people — not resumes, not bots.

Stay sharp. Stay skeptical. Don't give up.