What happens when the internet isn’t just for us anymore? When AI agents become the web’s second user, executing tasks and making decisions on our behalf, the rules of the game change. But are we prepared for this shift?
And while we’re at it—what does it really mean to make work more human? Is automation the answer, or are we losing something essential in the process?
This issue of AI Pulse doesn’t have all the answers, but it’s asking the right questions. Let’s explore.
Former Twitter CEO Parag Agrawal recently described AI as becoming "the web's second user" which is a shift that could redefine how the internet itself works.
For decades, the web was built for humans browsing websites and apps. AI agents have fundamentally different needs: they execute tasks, retrieve information, call APIs, and increasingly act autonomously on our behalf.
As the internet evolves from a network of websites into a network of AI agents, a critical question emerges: how do we ensure these systems remain transparent, accountable, and trustworthy? Want to understand what AI governance actually means and why it matters more than ever in the age of AI agents? Watch the first episode of our newly relaunched podcast, where we break down the fundamentals and explore what's at stake.
As someone who spends their days championing AI's potential, I'd be lying if I said I had no reservations — not about AI itself, but about society’s collective approach to it. Are we building toward something better, or just fueling a hype? Will we look back and realize we let a tech bubble reshape what it means to be human? Nobody knows. We're all learning in real time.
But amid the uncertainty, I am positive that re-keying invoice data or chasing down missing fields in a claim form is not what gives employees a sense of meaning and contribution. That friction—repetitive, debilitating, invisible—doesn't build character. It drains motivation.
There's a difference between the friction of a bureaucratic expense report and the friction of a difficult client conversation. The first steals time from being human. The second IS being human. Automating document processing makes space for the experiences worth having. It returns focus, judgment, and the room to think critically about work that actually matters.
Not a blueprint for society's future, just a practical way to use powerful technology to make work more human, right now.
There's a common assumption that AI governance slows things down. But research from IBM Institute for Business Value suggests it actually accelerates AI performance. - 27% of AI efficiency gains are attributable to strong governance - Companies investing more in AI ethics report 34% higher operating profit from AI -️ 1 in 4 failed AI initiatives trace back to weak oversight
The disconnect is striking. Nearly every organization surveyed plans to deploy advanced AI within the next year, but 58% admit they lack the data and governance foundations to support it. That's not a minor gap. It's a structural vulnerability.
The organizations that will scale AI successfully aren't the ones moving fastest. They're the ones who've built the foundation to move fast responsibly with AI.
A single autonomous AI agent breached each of the internal AI platforms of McKinsey & Company, Boston Consulting Group (BCG), and Bain & Company in hours. The fastest took exactly 18 minutes.
CodeWall conducted the research in accordance with responsible disclosure principles.
AI by the Numbers
14% Drop in hiring of workers aged 22–25 into AI-exposed occupations since ChatGPT's release—while overall unemployment in those same roles remains statistically unchanged. AI isn't eliminating jobs. But it may be quietly closing the entry points that build tomorrow's senior talent.
Organizations that embed document integrity into the front of their processes can reduce fraud exposure, improve operational efficiency, and meet increasingly complex regulatory expectations. This ebook provides a framework for achieving this.
The latest season of the AI Pulse Podcast is here, bringing together industry leaders to break down the biggest trends shaping AI and intelligent automation today. Designed to make complex topics more tangible and accessible, each episode will offer practical insights to help you stay informed and ahead of the curve as AI continues to transform the enterprise landscape.
AI in Practice: Real-World Applications & Case Studies
Learn how Connells Group Saved £115K Annually
By partnering with ABBYY and SS&C Blue Prism, real estate agency Connells Group built an end-to-end intelligent automation solution that now processes thousands of invoices each month, saving time and money. Discover how they did it.
Join ABBYY and FinTrU for an exclusive and interactive virtual roundtable bringing together financial services leaders. Discover how intelligent automation and document intelligence capability can help financial institutions modernize KYC workflows, reduce operational friction, and strengthen regulatory readiness. This invite is by invite only.
Risky Future Demo Day, Hosted by Insurance Journal – July 8 – 1 PM ET
Join ABBYY for this fun, virtual event featuring actionable demos for the insurance industry. The topic for this session is “AI Tools for Underwriting”. It’s a free event open to all insurance organizations.
As part of the ongoing event series, ABBYY Ascend will bring together enterprise AI leaders who are ready to turn complexity into clarity. Expect new product announcements, expert-led discussions, and unique insights tailored to each market. Across three cities, attendees will learn how to operationalize and scale successful AI systems.
ParaScript & ABBYY team up on document intelligence
The partnership brings together ABBYY's optical character recognition and intelligent document processing software with ParaScript's handwriting recognition and fraud detection tools. The combined offering is intended to create a single document intelligence workflow for organisations handling large volumes of printed and handwritten material.
Why Generic AI Falls Short in Healthcare Claims Processing
LLMs often fall short in complex, regulated healthcare workflows due to a lack of operational context and the risk of inaccuracies. See how purpose-built AI provides a more effective solution.
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