Automation Anywhere

Automation Anywhere Automation Anywhere is the #1 provider of agentic automation. https://linktr.ee/automationanywhere
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Providing agentic automation to autonomously run mission-critical processes, empowering employees to focus on what matters most.

08/31/2026

What happens to healthcare when a century of change arrives in five years? Richard Mitchell, CEO of University Hospitals of Leicester, one of the largest trusts in the NHS, gave our CEO Mihir Shukla a candid answer.

Part of it: agentic AI. Richard puts the return on his work with it so far at roughly 3:1.
One proof point: recruitment and onboarding. The trust's process used to run almost entirely on paper. Automation Anywhere bots now handle it, and Richard says both time-to-join and new-starter satisfaction have improved sharply.

He's balancing that against two other priorities that rarely move at the same pace: patient care and staying inside an NHS budget set by taxation.

Watch the full conversation below.

08/28/2026

"Every person in an organization is negotiating with themselves right now."

Our CEO, Mihir Shukla, said that answering a question on who The Five-Year Century is actually written for. He says the book is for decision-makers and change agents at every level, whether the change starts with one person, a team, or an entire company.

That negotiation is the book's whole argument, playing out at the individual level. Demographic decline, stalled productivity, and the pace of AI adoption are compressing a century of workplace change into the next five years. Mihir and co-author Nancy Hauge argue leaders now face a choice: reshape technology to fit how people actually work, or reshape people to fit whatever the technology demands.

Find out more about the 5 year century & watch the full episode of the Agentic Edge: https://ow.ly/STWS50ZGGHB

10,000 hours. That's what AXIA Energia recovered, and it started with a decision about DWG files.65,000+ technical docum...
08/26/2026

10,000 hours. That's what AXIA Energia recovered, and it started with a decision about DWG files.

65,000+ technical documents a year, many in engineering formats the prior manual process couldn't handle consistently. The compliance function couldn't scale by adding people. So AXIA rebuilt it instead.

Automation 360, Document Automation, and AI Agents, integrated with Gemini via Vertex AI, now handle ingestion, classification, validation, and reporting across the full document estate. The DWG files included. Ninety percent of manual effort gone. $265K in annual savings. Audit specialists focused on the judgement calls regulators actually care about.

AXIA's compliance function now absorbs new asset classes, regulatory changes, and group-wide expansion without rebuilding each time. Build the audit function right, and it becomes a platform the business grows into.

Growth doesn't create a capacity problem when the platform is built to scale. That's the compounding return, and it's the case for getting the architecture right first, especially in regulated industries.

Full case study, with Vitor Paulo Correia's take on what changed: https://ow.ly/H9B150ZFTGF

08/25/2026

Deciding where to start is the hardest part of any automation program, and Karen Ceesay, Deputy Chief People Officer at University Hospitals of Leicester NHS Trust, found the answer was simpler than most expect.

They started with the tasks nobody wanted to do.

One-click rejection emails. High-volume, repetitive, low-value work that never required human judgment. Recruitment teams processed it manually every single day, only because no one had removed it from their plate yet.

Wave one focused on building trust with the technology, freeing up capacity, and giving the team room to start operating as recruitment business partners rather than administrators.

Wave two scaled that logic further. Wave three transformation is where they're headed now.

The ambition: to become the first autonomous HR people services operation in the NHS.

The full conversation with Karen is available on demand.

https://ow.ly/i2Ov50ZFicA

08/18/2026

A broker submission arrives. Before an underwriter touches it, the AI agent has already run the full intake: email parsed, attachments downloaded (including handwritten documents), CRM checked for duplicates, opportunity record created, submission folder built in SharePoint or S3, triage run against quick-decline categories, every mandatory field extracted, anything missing automatically requested from the broker.

In-appetite submissions get a drafted underwriting narrative, a populated pricing sheet, a calculated technical premium, and a quote sent to the broker. Out-of-appetite submissions get an instant polite declination with the reason why.

That sequence runs in minutes.

The bottleneck in commercial underwriting was the chain of re-entries and routing steps that had to happen before an underwriter could get to it, not the risk judgment itself. A process reasoning engine orchestrates that entire sequence across CRM, document systems, and pricing tools, with zero swivel chair work.

Only 7% of insurance providers have scaled AI this way. For most, the models are running, but the ex*****on layer that carries their output through to a closed process isn't.

Watch the full underwriting demo. Insurance use case and implementation breakdown on the blog: https://ow.ly/JcbB50ZB3pI

What's the step in your underwriting workflow that still runs on email and manual re-entry?

08/14/2026

Stop measuring automation in hours.

That's the recommendation from Morgan Roberts, Senior Manager of Business Process Automation at ResMed. Most automation programs default to counting hours saved. Morgan starts somewhere else entirely.

ResMed runs its program as an enablement center: solve the operational problem first, then bring in automation. Technology is "the last layer," brought in once the business problem is clearly defined.

The real question is what you're actually trying to move: top-line growth, faster time to close the books, freed-up cash flow, a lower DSO. Each points to a different priority, and none of them show up on a straightforward hours report.

Commit to the outcome. Put it in writing. Then follow through.

08/12/2026

We just shipped .41, and there's a lot to be excited about.

Micah Smith, VP of Developer Relations, Community & Learning, walks through his 6 favorite features from this release. 👇

Spoilers below.
1️⃣ Operation Center gets custom, drag-and-drop dashboards. No more waiting on IT or rebuilding an Excel report every time you need to report on SLAs or work in flight.
2️⃣ AI agent governance and traceability. See exactly what an agent decided, which tools it called, and in what order. MCP extends that same visibility to third-party agents built in Agentforce or OpenAI.
3️⃣ Document evals in DocAuto. Compare extraction accuracy document by document or across a batch, version over version, benchmarked against expected results automatically.
4️⃣ Mozart Orchestrator improvements. Inline annotations, self-validating branches, quick-add search, and 12 new native connectors, including Databricks, Slack, Jira, Kafka, and Okta.
5️⃣ AI-driven knowledge updates in Aisera. Flag outdated or missing KB articles and get a ready-to-review draft pulled together automatically.
6️⃣ Package updates. Recorder improvements for RDP cloning, new OAuth support for
Salesforce, and updates to the Python package for API tasks.

08/11/2026

Laptop requests land in IT every week. Most are repetitive, and most don't need a human touching every step.

In this demo, Steven Spears walked through how an IT manager could set this up in minutes. He uploaded a single process document, and the agent came back already configured: persona set, edge cases mapped. Nothing built from scratch.

That same agent then ran the other side of the story. An employee's laptop couldn't keep up with their editing work anymore. The agent diagnosed it, built a personalized shortlist of three replacements based on the employee's role and usage, and pushed the order through SAP, Workday, and ServiceNow. The order went through without anyone touching a ticket or chasing an approver down. The employee's only job was picking a laptop.

This request needed a person exactly once: to make the choice, the AI service desk handled the rest.

https://ow.ly/hJnz50ZyFSF

One failed payment authorization opens a queue.Retries have timing windows. Settlement exceptions surface after customer...
08/07/2026

One failed payment authorization opens a queue.

Retries have timing windows. Settlement exceptions surface after customer-facing systems assume success. Reconciliation spans gateways, banks, and internal ledgers running on different schedules. Disputes arrive weeks later, with strict evidence deadlines.

At scale, the downstream work following a failed or ambiguous payment can exceed the operational cost of the original transaction. Most of it still moves through manual coordination between payments operations, treasury, and customer support.
Most payment systems, and most payment AI, treat authorization as the end state. It's where the tooling is mature. Everything after it is where operations teams live.

Agentic process automation closes that gap. APA agents persist across the full lifecycle, tracking payment state, responding to events like soft declines or settlement delays, and escalating to human reviewers when judgment is required. Every action is logged with policy context, creating the audit trail compliance and regulators require as AI becomes embedded in financial workflows.

Full lifecycle breakdown: https://ow.ly/yOSj50ZxKw6

Every day a clinical trial is delayed, a treatment stays out of reach.IQVIA is changing that. By partnering with Automat...
08/06/2026

Every day a clinical trial is delayed, a treatment stays out of reach.

IQVIA is changing that. By partnering with Automation Anywhere to transform its most data-intensive research operations, IQVIA achieved an 80% gain in patient analytics efficiency and is now detecting adverse events 30% faster, putting life-saving insights in the hands of researchers sooner than ever before.

This is what the Autonomous Enterprise looks like in life sciences: AI agents processing and validating clinical data at scale, human experts staying in the loop on what matters most, and the entire drug discovery process moving faster as a result.

The future of clinical innovation isn't just about better science. It's about removing every barrier between data and discovery.

Read IQVIA's full story: https://ow.ly/Vblh50ZxaXr

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