ABBYY

10/12/2026

Most AI projects don't fail because the technology doesn't work – they fail because two-thirds of your team were never really brought up to speed.

On the next episode of the AI Pulse podcast, we're sitting down with Dado Van Peteghem, strategist and author of Soul vs. Scale, to talk about why the human side of AI transformation matters as much as the technical side.

We'll be covering why change management might be more important than your AI strategy and the one question every leader should ask before their next AI investment.

📅 New episode dropping October 14th. Subscribe, so you don't miss it.🙌

✅ https://hubs.li/Q04zW_fW0

10/08/2026

For the past few years, the answer to almost every tech question has sounded the same:

"Move it to the cloud." For a lot of use cases, that works.

Until a regulator says the data can't leave a specific geography, or a customer demands stricter controls, or your legal, compliance, or security teams ask a simple question:

"Where exactly are these documents being processed?"

That's when cloud-only stops being a strategy and starts becoming a constraint.

With almost 40 years of comparing, classifying, extracting, and understanding documents, we've learned that real-world document processing is never one-size-fits-all. The organizations handling the most sensitive, complex information need flexibility, not ultimatums.

As AI adoption accelerates, businesses are discovering that the challenge isn't just extracting information from documents. It's doing it where business, regulatory, and security requirements allow.

That's exactly why we're paying attention to what's next.

Introducing FineParser.

A modern, containerized deployment model for document parsing design for AI. No cloud account. Runs on your infrastructure in minutes. Now available.

🔗 https://hubs.li/Q04zxDX20

10/07/2026

Ripping out legacy systems to make room for AI is often the most expensive way to fall behind.📉

In his new InformationWeek article, Jon Knisley, Director of AI Value Management at ABBYY, argues that your decades-old core systems are a competitive moat. They hold years of transaction history, edge-case handling, and regulatory logic that no startup can synthesize and no vendor can easily replicate.

Your legacy proves you've built something durable. Pair it with focused, well-governed AI, and you gain precision and speed that start-from-scratch competitors can't match.

📖 Read Jon's full article: https://hubs.li/Q04zsYLW0

🔍 See how ABBYY turns complex documents into AI-ready data: https://hubs.li/Q04zsYNF0

10/06/2026

AI solutions catch headlines, but what is the true differentiator in today's tech market?

Gina Ray, ABBYY Vice President of Corporate Marketing, argues that people are the real X factor when it comes to driving AI success. In her recent article in the Intelligent Enterprise, Gina explains that behind every AI breakthrough is a team of people making critical decisions and asking the right questions.

Is this the right tool for the job?

Can we prove it's accurate and at scale?

Will this hold up under scrutiny?

ABBYY leaders have been asking the tough questions and keeping people in the loop for more than 35 years, and it shows in the recognition from Gartner, Everest Group, IDC, and the 2026 AI Breakthrough Awards, where ABBYY was named intelligent document processing (IDP) Solution Provider of the Year. None of that came from deploying a model and hoping for the best. It came from purpose-built AI, applied to well-defined workflows, with human oversight at every stage.

The next phase of enterprise AI isn't about applying LLMs everywhere you can. It's about the discipline to decide where they belong.

Read Gina's full take here: https://hubs.li/Q04zm-xN0

10/05/2026

"Governance is not the thing slowing AI down. Weak governance is."

That single line from our Chief Compliance Officer, Roman Kilun, reframes the entire AI governance debate.

Here is the contradiction hiding in our 2026 State of Intelligent Automation report:

👉 70% of leaders say governance requirements are slowing their AI deployment.

👉 78% of leaders with established frameworks say governance has made their AI initiatives MORE successful.

Weak governance is what keeps AI stuck in pilot purgatory, while clear accountability, controls, and oversight are what move AI into production and turn it into real ROI.

Responsible AI is not a tax on speed. Done well, it delivers both.

The organizations that ask "Who Answers for AI?" before something goes wrong will be the ones that scale with confidence.

Read the blog for more details: 🔗 https://hubs.li/Q04zbhf-0

Download the full 2026 ABBYY report, Who Answers for AI: The Governance Gap, for the complete data and market-by-market breakdowns: [https://hubs.li/Q04zbhtT0]

10/05/2026

Regulators are treating fraud, AML, and KYC as one problem. Most institutions are still solving them as three.

AMLR and FATF guidance is accelerating that convergence, and the institutions getting ahead of it aren't just updating policy, they're rebuilding the document review layer underneath all three. Because the forgeries feeding fraud exposure, AML gaps, and KYC failures share the same root: documents your teams can't fully trust or process fast enough.

ABBYY, Naviant, and Resistant AI are bringing that conversation to Toronto; an invitation-only working dinner for senior leaders in banking, insurance, and fintech.

🎯 ABBYY Circles · Toronto
📅 Thursday, October 8, 2026 · 4:00–7:00 PM
🍁 Riley's Toronto, 155 Wellington St W

In three hours you'll see live forensics that detect tampering imperceptible to visual review, run a pKYC readiness check against AMLR and FATF guidance, and leave with a scored automation shortlist from our AVCP Masterclass. The room is designed for Chief Risk and Compliance Officers, Heads of KYC and Onboarding, and CIOs who own these challenges now.

Request your seat👉 https://hubs.li/Q04ypY_00

10/04/2026

Fraud, AML, and KYC are converging into one regulatory expectation. The documents at the center of all three are getting harder to trust. 📃🤔

For every $1 of fraud loss, financial services absorbs $5.75 in total costs. That multiplier compounds every time a forged document clears a review process that was never built to catch it.

ABBYY has spent 35 years turning unstructured documents into trusted, automated data flows. GenAI has raised the ceiling on what "forged" looks like, and Resistant AI's forensics identifies tampering imperceptible to visual review while Naviant brings specialized KYC expertise to help institutions stop document fraud at ingestion. Together, we're hosting a working lunch in Charlotte to show what that looks like, live.

🎯 ABBYY Circles · Charlotte
📅 Wednesday, October 7, 2026 · 12:30–3:30 PM
📍Capital Grille, 201 N. Tryon Street

An invitation-only session for senior leaders in banking, insurance, and fintech. Three hours. No broadcast. You'll leave with:

• A live forensics demo that surfaces forged files earlier and reduces false positives

• A pKYC readiness check against AMLR and FATF guidance, tailored to your institution

• A scored automation shortlist from our AVCP Masterclass — potential project value exceeding $1M

• Candid conversation with Chief Risk and Compliance executives, Heads of KYC, and CIOs across the Charlotte region

Seats are limited. Request your invitation here: https://hubs.li/Q04ypXTG0

10/01/2026

Creating a convincing fake ID once took specialized skills and physical materials. Not anymore.

Generative AI has put document fraud within reach of almost anyone. Templates get cloned. Bank statements get altered. Metadata gets tampered with, all at a speed and scale that traditional fraud controls were never built to handle.

That's the uncomfortable truth facing risk and compliance teams right now: the attacks have evolved, but most review processes haven't.

So how do you catch fraud that's designed to look flawless?

You stop relying on the human eye alone.

ABBYY combines Document AI with document forensics to shift the odds back in your favor by:
• Processing high volumes of documents accurately, without slowing operations to a crawl.
• Surfacing anomalies that isolated, manual review would miss entirely.
• Escalating only the cases that genuinely need human judgment.

The result is a smarter division of labor.

Machines handle the scale and pattern detection. 🤖

People apply the contextual judgment that automation cannot replicate. 🧠

Synthetic identities are only getting more convincing. Your defenses should be getting sharper.

Nick Carr, Director of Pre-Sales at ABBYY, explains how to detect document fraud in a world where anyone can manufacture a "real" document.

How confident are you that your current controls would catch a synthetic identity today? 🔗 Read the article: https://hubs.li/Q04yXkSM0

09/30/2026

Does AI cut through security alert noise, or just add to the pile?

That's the question Clayton C. Peddy, CISO at ABBYY, and Erika Dean, CISO at Tricentis, dig into on the latest InformationWeek Podcast: "Does AI Help or Trigger Alert Fatigue?"

They unpack what the alert cycle looked like before AI was introduced, whether AI improves the detection of false positives, and whether it is better to reduce the noise from alerts or to be hypervigilant with notifications for every potential security threat.

🎧 Listen here: https://hubs.li/Q04yL4rb0

A big thank you to InformationWeek and host Joao-Pierre S. Ruth for a sharp, candid conversation.

Learn about ABBYY’s AI privacy and security practices in the ABBYY Trust Center: https://hubs.li/Q04yL4Vr0

How has AI changed alert fatigue for your team?

Erika Dean, CISO at Tricentis, and Clayton C. Peddy, CISO at ABBYY talk about how AI can be part of a layered security strategy.

09/30/2026

Everyone loves demo dreamland - the parser handles the sample PDF perfectly, the text is clean, the tables look sharp, and the output flows neatly into your AI pipeline.

Then production happens and you can kiss consistency goodbye. 👋

Your invoices arrive skewed, contracts are scanned copies of scanned copies, and financial reports suddenly switch between languages. Somewhere, a table loses its structure, a key clause ends up in the wrong section, and your AI starts making decisions based on incomplete information.

Nothing broke overnight, it happened one document at a time.

So now the data entering the system isn't trustworthy, neither are your outputs, and you're left with one question: how does your parser perform when it's confronted with the real, messy, inconsistent documents you actually manage.

Before you trust a parser with production workloads, make sure you're evaluating it the same way production will.

Ready to see the difference of an enterprise-grade document parser with predictable data structure?

Try FineParser. See the difference it makes for your RAG pipelines.

Get access today! No cloud account needed. Runs on your infrastructure in minutes.

🔗 https://hubs.li/Q04yJ64T0