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Belgium 10-3-26 All Members Physical english

The Composable Enterprise: Engineered with AI

From modular business design to AI-driven pipelines, architectures, and operationsA composable enterprise is built on modular processes, API-driven ecosystems, low-code platforms, and cloud-native services. It promises speed and adaptability by allowing organisations to reconfigure their capabilities as conditions change. However, modular design alone does not guarantee resilience; the way these systems are engineered and operated is just as important.This is where AI is beginning to make a difference. Beyond generating snippets of code, AI is already influencing how entire systems are developed and run: accelerating CI/CD pipelines, improving test coverage, optimising Infrastructure-as-Code, sharpening observability, and even shaping architectural decisions. These changes directly affect how quickly new business components can be deployed, connected, and retired.In this session, we will examine how CIOs can bring these two movements together:Composable design is the framework for flexibility and modularity.AI-augmented engineering is the force that delivers the speed, quality, and intelligence needed to sustain it.The pitfalls of treating them in isolation: composability that collapses under slow engineering cycles, or AI that only adds complexity without a modular structure.The discussion goes beyond concepts to practical implications: how to architect organisations that can be recomposed at speed, without losing control or reliability. The outcome is an enterprise that is not only modular in design but also engineered to adapt continuously under real-world conditions.

Belgium 12-3-26 Physical english

The Third-Party Risk Reckoning: How far can you trust your vendors?

Tomato! Tomato! Tomato! Get your tomato now! Every vendor sells security. And every company depends on vendors, partners, and suppliers. The more digital the business becomes, the longer that list grows, and so does the attack surface. One weak link, and there is always one, or one missed update, and trust collapses faster than any firewall can react. What used to be a procurement checklist has become a full-time discipline. Questionnaires, audits, and endless documentation prove that everyone’s “compliant,” yet incidents keep happening. So it’s clear: the issue isn’t lack of policy, or maybe a bit, but mostly lack of visibility. Beyond a certain point, even the most secure organisation is only as safe as its least prepared partner (or an employee who hadn’t had their morning coffee). So how far can you trust your vendors? How do you check what you can’t control? And when does assurance become theatre instead of protection? Does it come at a different cost? Let’s exchange what works and what fails in third-party risk management: live monitoring, shared responsibility models, contractual levers, and the reality of building trust in a chain you don’t own. A closed conversation for those redefining what partnership means when risk is shared but accountability isn’t.

Belgium 19-3-26 Country Members Physical french

Vendor Detox: La consolidation vaut-elle le risque ?

Moins de Partenaires : La consolidation vaut-elle le risque ? Le problème est la prolifération des fournisseurs : trop d'outils causant de la complexité, une taxe d'intégration paralysante et de la redondance. La Taxe d'Intégration est le coût caché (en temps, en échecs et en ressources) d'essayer de faire fonctionner ensemble des systèmes disparates. Cet échange se concentre sur des stratégies éprouvées pour simplifier de manière agressive le parc technologique, consolider les fournisseurs et élever certains fournisseurs clés au rang de partenaires stratégiques.

March 12, 2026 Squad Session Invitation Only Physical english

The Third-Party Risk Reckoning: How far can you trust your vendors?

March 24, 2026 Squad Session Invitation Only Physical english

Killing Zombie Projects: Knowing when to stop, restart, or quietly let go

Every organisation has them, projects that keep running long after their purpose has faded. No one remembers who asked for them, but shutting them down feels riskier than keeping them alive. And eventually, people stay assigned, budgets stay allocated, and energy drains into work that no longer matters. Inertia at its finest.

March 26, 2026 Squad Session Invitation Only Physical english

Measuring Value in AI Initiatives: Defining ROI, accountability, and measurable outcomes in complex environments

AI projects continue to multiply, but proving their value remains difficult. Most organisations can track activity, not impact. Dashboards count pilots and models, yet few translate to measurable business outcomes. The result is familiar: success stories without clarity on what they actually delivered.

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AT&T embraces intelligent automation at scale

Six years into its robotic process automation journey, AT&T has implemented more than 3,000 bots, developed an automation center of excellence, and realized a 20x return on investment.

For CIOs riding today’s rising wave of robotic process automation (RPA), leading-edge adopters whose mature implementations have paid off can provide invaluable lessons about how to make the best of the technology and where its use can lead.

Telecom titan AT&T is one such enterprise, having began RPA trials in 2015 to reduce repetitive tasks for its service delivery group, which had a large volume of circuits to add at the time, as well as various services in play for provisioning networks, says Mark Austin, vice president of data science at AT&T.

“These things would come in large batches, and they would have Excel files and people were literally typing these things in individually into the systems because they weren’t set up for batch,” Austin says. “We heard about RPA at the time, and we started trying it and all of a sudden we were able to automate one process and then the next process and it kind of grew from there.”

With the technology in its early days, the first thing AT&T IT did was go to its compliance and security experts for guidance on governing RPA, which helped the team make its automation tools stable and secure. The next step was to win the battle for hearts and minds within the company by turning skeptics into believers that automation could make employees’ lives better. Initial efforts focused on addressing unpopular, monotonous tasks such as order entry.

The pilots helped demonstrate how automation could fit into daily operations and workflows.

Within a year, AT&T had implemented 350 automation bots. More than six years into its RPA journey, AT&T has implemented more than 3,000 automation bots. Austin says RPA has helped AT&T recognize hundreds of millions of dollars in annualized value, saved 16.9 million minutes of manual effort each year, and shown a 20x return on investment.

Taking RPA to the next level

Mark Austin, vice president of data science, AT&T

With RPA ingrained in its business process DNA, AT&T opted to combine automation with data science and the chief data office because it believes the future is in smarter bots that leverage AI functionality, such as OCR or natural language processing (NLP), an emerging strategy often referred to as intelligent automation.

“Tying those things together is pretty powerful,” says Austin, who runs AT&T’s data science, AI, and automation group.

By way of example, Austin points to what he considers one of the company’s biggest RPA successes: a bot his group has created that uses OCR to scan vehicle registration documents and NLP to understand those documents and any necessary actions AT&T must take in support of more than 10,000 technician vehicles, one of the largest vehicle fleets in the US. If payments are required, the bot can also trigger the payment process.

Being able to create automation bots such as these was invaluable when the COVID-19 pandemic first hit, Austin says.

“There were a lot of customers that were calling and saying they wanted to move the charges from this org to that org in their company,” Austin says. “Someone might call up and say they wanted to move 5,000 lines. What we do now is we have them interface with [interactive voice response (IVR)]. The IVR detects what they want to do and then it triggers a bot to send them a secure form to fill out. They fill out the form, submit that back, and we run the bot to automate the process to get it going.”

The company has also rolled out bots to help customers avoid overage charges. One such bot monitors usage of AT&T’s integrated voice, video, messaging, and meeting services, more than 21,000 records per minute, looking for overage charges above a pre-set amount. If it encounters one, it automatically notifies the customer and the assigned AT&T sales rep.

Codifying RPA best practices

After the first year of pilots, with demand for RPA spreading rapidly through the business, AT&T created an automation center of excellence (COE) to accelerate implementation.

“When you’re the size of AT&T, and you’ve had so many mergers and so many systems, there’s just lots of manual processes,” Austin says, explaining why it was essential to create a COE that could focus on implementing automation throughout the organization.

The centralized automation team now boasts 20 full-time employees and some contractors as well. Austin notes that the real secret to successfully scaling automation is spreading RPA knowledge throughout the organization. The COE helps develop, deploy, manage, measure, and enable automation projects across AT&T. More importantly, it seeks to educate subject matter experts in automating their own tasks and processes.

“Pretty early on, we figured out that if you really want to scale, you’ve got to move to training others how to do it, teach them how to fish, so to speak,” Austin says. “Ninety-two percent of everything we do with the 3,000 bots is done outside of my team. If you’re not an IT person, it’s maybe 40 hours of training.”

The company has trained more than 2,000 citizen RPA developers who have built the lion’s share of AT&T’s 3,000 automation bots. To support them, the company has created a “Bot Marketplace” where citizen developers can “shop” for ready-to-use tools and support to get their automation solutions up and running. The marketplace stores and shares low-code and no-code automation solutions and tools. It now adds roughly 75 new blueprints of reusable automation components every month.

As RPA knowledge has spread, Austin says the lines of business have started forming their own automation teams, creating a hybrid model in which the COE provides tools and support, while front-line teams in the lines of business implement automation.

“They even have some new job titles popping up,” Austin says. “We’ve got a couple process automation managers and automation developers that we’re seeing out there. On our team, we’re continuing to move to automate the process, the platform, and then tie in the data science side.”

When it comes to lessons learned, Austin has some advice for others out there who may be starting their RPA journey. First, start small and get some wins. Second, don’t try to keep things centralized. While the center of excellence has been essential to AT&T’s RPA journey, just as important has been democratizing the effort to scale the proliferation of automation within the company. Finally, evangelization is important. AT&T has created an internal automation summit where groups can present their automation projects to the rest of the company, show off their successes, and help spark new ideas.

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