When the stakes are high, proven solutions are way more valuable than flashes of maverick genius. Thankfully, ABBYY’s 2025 London AI Summit was packed with enterprise-level insights and pragmatism.
Even though it covered many ideas, key themes emerged. Chief among these were two concepts often glossed over in favour of wow moments: privacy and compliance.
The opening panel was unanimous that AI processes must be explainable. This is partly a matter of law but also about staying in control of the tech.
For instance, agents and LLMs tend to behave erratically. Relying on them 100% is like expecting a bright toddler to run the lunch hall, so the speakers clarified how to choose the right tool for the job.
The message was clear. To deploy the full power of AI, we must keep the mission clear and the data clean. I learned a lot about how to make this happen in the real world.
AGI Is a Vision — Enterprise AI Needs to Deliver Now
The idea of Artificial General Intelligence (AGI) is captivating - but today’s enterprise challenges require something more grounded. In areas like KYC, prior authorization, or logistics, success depends on understanding documents and the structured processes they drive. These aren’t just prompt-based problems. These processes unfold over time, across departments and systems, and within strict regulatory frameworks. Success requires AI that can not only extract meaning from unstructured content but also interpret it in the context of business logic, process flows, and outcomes. While AGI remains a long-term pursuit, real business impact today comes from purpose-built AI - solutions that combine Document and Process Intelligence to deliver accuracy, accountability, and measurable outcomes.
Ever feel like we’ve already reached AGI when chatting with your favorite chatbot—empathetic, articulate, almost like a dear friend? It’s easy to forget Generative AI isn’t thinking; it’s predicting. According to recent research as it grows more capable, it also hallucinates more—confidently producing false information. Even OpenAI admits it doesn’t fully understand why (speaking of explainability), and researchers believe the issue may never be solved. So what should businesses do? Ignoring GenAI isn’t realistic—it’s already transforming workflows and sparking innovation. The solution is grounding—connecting it to reliable, verifiable data. Let it create and support, but always tether it to the facts to protect accuracy and trust.
China has officially launched Agent Hospital, the world’s first AI-powered virtual hospital.
There are 42 AI doctors operating across 21 departments like pediatrics, cardiology and neurology working the end-to-end journey from illness onset through diagnosis to discharge. The agents are capable of treating 10,000 patients in days — something that would take human doctors over two years
Plus, the AI doctors reached an impressive 93% accuracy rate for respiratory diseases on the US-based MedQA benchmark.
LeNet-1, built at Bell Labs in the late '80s, was the first convolutional neural network (CNN) to recognize handwritten digits with impressive speed and accuracy. Running on a PC with a powerful DSP chip, it could read ZIP codes in real time—a big deal back then. Trained by Yann LeCun’s team, it became one of the first real-world AI success stories and helped pave the way for today’s deep learning. Scry AI - YouTube.
Only 25% of AI initiatives have met ROI expectations, according to CEOs surveyed by the IBM Institute for Business Value. Meanwhile, organizations have achieved enterprise-wide rollouts with only 16% of AI projects.
CEOs may be reconsidering how they adopt AI. Only 37% of the CEOs said it’s better to be “fast and wrong” than “right and slow” when adopting new technologies — a shift from gen AI’s early days.
Purpose-built AI for invoice processing makes it easy to streamline your AP processes globally. This multinational snack food supplier scaled their processes across 20 markets without having to hire new headcount.
New episode: From Prototype to Production, How to Apply and How to Deploy Generative AI Securely
Tune in to understand how to leverage AI to enhance business processes, the importance of maintaining human involvement, and the ethical considerations necessary for responsible AI deployment.
New blog: ABBYY Releases New AI Risk Management Policy
The ABBYY AI Risk Management Policy establishes guidelines and processes for managing risks associated with AI in compliance with applicable legal and AI risk management frameworks. Read the blog to learn what that entails.
Join us for ABBYY Developer Conference 2025 in Bengaluru – a two-day, in-person experience that brings together developers, engineers, business leaders, and automation enthusiasts.
In case you missed it or want a rewind, Ascend is ABBYY’s virtual event where AI-powered automation gets real and moves beyond the hype. See why it’s themed “Clarity Compiled” as we turn complexity into clarity.
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