Hi there “Process Automation” fans,
Welcome to a new installment of “Process Automation” tips.
This post will give you a “key-notes” update of the ‘OpenText World (Nashville, Tennessee) online 2025’ event from last month (November 17-20, 2025)! A multi-day event physically happening in Nashville, Tennessee with lots of sharing sessions to join. I did not join the party in the United States (yet!) but signed myself in for the online pass. The pass is free and gives access to the key-notes of the events. Let’s see what value we can grab.
Let’s get right into it…
With OpenText, there is a shift going on with lots of new things:
- Moving from “Las Vegas” to “Nashville”
- Moving to the theater of LinkedIn (later I also found the regular Virtual eXperience)
- The replacement of Mark J. Barrenechea (CEO/CTO) with interim CEO James McGourlay; Read more here and here
- “Organic growth” for the company with more product focus (which is a good thing in my opinion)
- OpenText is now “faster”, “bolder”, AND “purpose driven”!
My virtual registration gives access to the two main keynote sessions. The week after I normally see more keynotes passing by, but for me personally not worth the time to go through. It’s mostly the same information with high sales content where I’m just a “techie”! 🤓
These are some impressions of the “Elevate (and engage) together” eXperience which is the theme for this year:
Some “Nashville” facts:
- Iconic place - Where artists write their next big hits and dreamers become doers.
- Music City - Where you find the heart of country music and home to the Grand Ole Opry and the Country Music Hall of Fame.
- Broadway Street - Famous for its live-music bars (“honky-tonks”) where bands play from early morning to late night.
- The Parthenon - Nashville has a full-scale replica of the Parthenon from Athens, built in 1897.
- Healthcare hub - Besides music, Nashville is one of the biggest healthcare industry centers in the US.
Here is Aviator “Ice” and the “The Icebreakers”:
Watch also out for #opentextworld2025!
Time to consume the keynotes…From the new interim CEO James McGourlay…Good luck!
“Inspiration” day 1 - recap here
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We always start with a great thank you to the customers and sponsors (see at the end of this post)
James McGourlay; A CEO of many roles within OpenText for the last 20 years. So, he saw it all (IT, customer support, PS, and sales); even his kids friends start with OpenText as first/second job.
Elevate together; Engage, come, and work together with exchanging ideas and parties at OT World.
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Bring the best in every organization by empowering individuals to see information in new ways (the human potential!).
Information management touches our every day (OT is everywhere with digital eXperiences):
- Getting milk for your coffee
- Reading new on your cell phone
- Paying a bill for your family
- Seeing a doctor to get medicine
- Turning on TV to stream a movie
Do you have “information”; OpenText will make it smarter, safer, and actionable!
OpenText Next Generation Solutions:
- Business clouds - All functions we serve, like automation, unification, and security.
- OpenText Aviator - Not just AI; It’s the digital knowledge worker (human and AI)!
- OpenText Cloud Platform (OCP) - Infrastructure and cloud operations to save data private and secure (at global scale).
- OpenText Services - To support it all with the success team to get value for the customers.
We don’t create LLMs, but we guide the customers to translate (un)structured data into tangible business outcomes with AI using multiple models with open architectures for secure data management over APIs.
The guidance principles of AI aviator - It’s multi-cloud, multi-model, and multi-application!
Secure information for AI…OpenText has:
- …over 400 AI-related patents
- …decades of innovation
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Enterprises need to look at their own data:
- Behind the firewalls (the part of the iceberg below the sea-level) is much more data.
- For great AI at the highest levels, you require solid data.
Strong Data Foundation = Strong AI Outcomes
How to turn the hype of AI into a practical, usable use-case? Everyone has great ideas, but how to use it?
Wise words: Micro-moments is where customer satisfaction is created! Can we detect these “micro-moments” with basic machine algorithms, rules sets, and workflows? NOPE, they can NOT detect anything from incidents in the past, apply learning/context to it, and use it to send an alert out. Agents solve this when you chain them together.
Domain specific agents for mission specific tasks:
- RCA Agent
- False Positive Agent
- Ticket Agent
- Translation agent
- Release Notes Agent
- Contract Review Agent
- etc.
What if you have a hundred of them? Secure AI Agent for every critical process with the orchestration of agents. Every knowledge worker with their own small army of agents.
We can do this with a platform…
It requires trust with 100% correct answers
It requires data with entitlement where access is defined and controlled
Without context in AI, it leads to failure
Without data, there is no context. Without context, enterprise AI fails.
We (from OpenText) bring life into your data and add context to it:
- What knowledge do you want your AI agents to have?
- What policies guide their behavior?
- What decisions are they allowed to make?
Designing a system to maximize data and AI with data lineage, data usage rights, and data redaction & retention. Secure information management for AI!
Secure, trusted, open, and compliant platform 👉 OpenText AI Data Platform (AIDP) (knowledge discovery)
It’s an “open” platform which means connecting all these levels of solutions within your enterprise:
- at agent level
- at API level
- at orchestrator level
- at data level
- at knowledge graph level
The (work)flow is simple:
“Data sources” > “Knowledge discovery” > “Data products” > “Security, compliance, governance” > “Relational knowledge mapping” > “AI control plane”
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Framework to put it all together and making AI practical for the enterprise:
- Discover: “Knowledge discovery” with connectors to read a variety for file-types. Eventually you can do an “Enterprise Search” on all the data.
- Connect: Unify data from a “Data Product Directory” (structured high-quality data cleaned from mess applied with the controllable rules). It’s the new masterdata with correct metadata as input for an AI agent in the correct context. “Knowledge Graph” understands relations between data (structured and unstructured).
- Act: “OpenText Aviator Studio” (in
26.2) for monitoring and scale the army for agents (as agent lifecycle management). It’s part of the AI Data Platform where you create workflows and orchestrate your army of AI agents. - Govern: “Content Aviator” for occurency of correct data and asking accurate questions about it.
- Monitor: For security and making sure the AI agents do the job correctly with “Extended OpenText AI security” and “Guardrails security”.
“Evaluation frameworks” are needed to measure the accuracy of your agents. You have several products, but the one that rules them all is (of-course) from OpenText and is named “Aviator EvalOps” (as part of the Aviator platform)
All nice and great, but how do we deploy and scale this all? In short, we (from OpenText) create this all for you in the correct cloud zone, so YOU can get access to it in your own environment? #HOW, #WHAT, #WHEN? Over VPN tunnels and open firewalls!? 🙃 Let’s see how the iceberg (the part underwater) will open its secrets…I think we all know the answer already!
Finally, “OpenText Aviator AI Services”; ‘Professional Services’ and ‘Former Deployment Engineers’ teams to support your AI journey. It’s consultancy next level to help you to embrace AI within your enterprise.
Summary for the future for the “OpenText AI Data Platform”:
- AI Control Plane
- Relational Knowledge Mapping
- Security, Compliance, Governance
- Data Products
- Knowledge Discovery
- Data Sources
The roadmap builds forward on all the information OpenText gained from the last 30+ years and connects the dots between all these business applications:
Final wise words from Savinay Berry:
- We move from “content in context” to “AI in context”
- The risk of inaction (if you don’t jump on the AI-train) #ISN’T_THAT_CONCERNING
- Agents will live on their own without interaction. Make sure to orchestrate it all at the finest level within your company.
Welcome to “THE NEW OPENTEXT”!
“Activation” day 2 - recap here or here
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Quick recap to avoid the agent sprawl across the enterprise. Make sure to correctly implement your Agent Lifecycle Management (for managing the army of AI agents):Conception -> Governance -> Monitoring -> Retire
Customer eXperiences about their ALM:
- IBM: AskHR tool to introduce generative AI with chatbots to employees which moves to a (domain specific) agentic AI with WatsonX. Agent collaboration is key here for a unified eXperiences to the end-users.
- United Airlines: Reliability and safety is top priority (get to the truth fast!). AI needs to scale the diagnostic cycle for this. It’s a processing flow between AI Triage Agent, Custom Diagnostic Agent, and the Content Aviator AI of OpenText.
- Pick n Pay: DevOps Aviator (delivery and deployment platform) to get software into production at scale. For this you want to create userstories fast and testcases with detailed steps. It’s all in context of the enterprise data (including video data).
- Honda: Trading Grid Online on failed transactions takes a long time. Aviator Studio can do this now faster and at scale introduction a minimal downtime with an adaptive context-aware and self-learning automation.
- SLB: Monitoring and logging at scale. You want to resolve a problem quickly (problem -> diagnose -> resolve). AI powered root cause analysis can create a topology with event details based on company data (the context). Aviator can answer questions on these events to quickly get to the root cause of the problem.
Good to understand: On the OpenText AI data platform, OT will create its own agents. Customers can add their agents too and that’s where the orchestration starts to bring value over workflows that chain the army or agents with global content (from the world) and domain specific content (from the customer).
The steps of Aviator Studio implementation:
- Create an Agent
- Set name and description
- Define tasks and goals (for the agent)
- Add tools
- Add knowledge sources
- Save agent
- Assemble Agents into a Workflow
- Add agents to workflow
- Define tasks and goals (for the workflow)
- Testing Agents
- Select an agent and simulate it
- View agent progress and results
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The greatest concept to bring practical AI to the enterprise 👉 ECOSYSTEM
You can’t do it alone and with partners we solve it together:
Domain specific agents require data; The bigger, the better. The cleaner, the smarter. Gemini3 (by Google) is available with multi-modality and complex reasoning. Notion of thrust is important; The AI must be transparent and explainable. Reliable, repeatable, resilient, private, secure, and fearless are keywords for a trustworthy AI.
Is the “agent orchestrator” equal to an “agent manager”? Tracing if the agent did the correct thing is only possible with proper auditing (based on your business rules). Governance as code…Where we try to adapt to the frame of AI which takes ages! We need to move to AI governance, but watch out for overengineering and the risks you don’t understand.
The future in two years? deploy agents in production fast with platform like Aviator Studio orchestrating agents in a workflow. Scaling is not the lack of tools, but how clean is your data…Ohw, and commercializing quantum computing! Will that be the ultimate operating model or the captain of the AI agent’s army? Who knows…
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Trust at our Core:
- Data you can rely on.
- Technology that performs.
- 22K OpenTexters delivering for 330K customers.
Customer zero (Efficient, High Quality, Cost effective, AND trusted data & AI):
TRUST; Without innovation leaves us stuck.
INNOVATION; Without trust leaves us exposed.
Valid questions to ask yourself are:
- Is our data ready?
- Can we trust our AI outcomes?
- Can we run AI with confidence?
- Can we prove AI’s value?
Good (trusted) Data = Good AI 👉 “OT Trusts OT”
Humans set the direction; Agents deliver the acceleration:
What keeps you up at night?
- Software & systems complexity? > Systems, Tools & hardware rationalization
- Rising vendor costs? > Process improvement, automation & AI
- Hybrid & secure cloud ecosystems? > Data center consolidation & cloud optimization
- Cyber risks? > 100% managed security
- Operational efficiency? > Employee productivity
Trust and innovation don’t compete; They strengthen each-other, and it all starts with trusted data…
Trust, TRust, TRUst, TRUSt, TRUST…I think the message is clear by now! 🙃
Let’s elevate together!
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We know Muhi from his “Technology Innovation Keynotes” in the past, but it looks like he moved into the security side of products with still a good talk on the stage.
The ultimate driving machines at BMW (Sheer Driving Pleasure). Core Delivery platform for machine delivery across over 140 countries. AI automates repetitive tasks, and the data lake makes the employees analyze it all (instead of data hunting). It helps in efficiency and faster problem-solving with AI driver services (Q-chat). They see AI as an opportunity and not as a risk. Using AI is an improvement process across the enterprise. Cars as just computers on four wheels with 500M lines of code on-board.
Sponsors
What do you do without sponsors (if you have an annual revenue of $5.168B in 2025!):
Next year, OpenText World will be in Orlanda Florida (the week of Oct 19th, 2026)!
That’s a “DONE”…In short: AI will bring value to your enterprise, but make sure it’s clean from garbage! Well, that’s what I shout already since my “4-year anniversary post in 2023” > “Crap in, is crap out”. Even OpenText quotes about it since 2023 > “Great AI starts with great Information Management”. Fascinating, especially when you read this quote from a colleague of mine: “Everyone wants change, but no one wants to change!”! It’s a wrap my friends; Have a great weekend, and we see each-other in another great topic about Process Automation Tips. Cheers!
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