AI agents
Customer service
Technologies
This year’s Web Summit in Lisbon highlighted that AI is no longer just an emerging idea; it is becoming the essential infrastructure for the business and industrial landscape of the future.
The innovations presented by Microsoft, NVIDIA, and Siemens and the polished prototypes from Decagon, Glean, and Superhuman — were undeniably impressive. Yet what stood out even more was the focus on practicality. Panel after panel, from industry leaders to scale-ups like Wayflyer, bunq, and Uber, converged on a single message:
Real AI impact comes from solving real-world problems and enhancing humans work, at scale, with trust and businesses collaboration at the centre.
Brands across sectors, from Amazon and TikTok, to Yanolja Cloud, Oura, Cloudflare, and Pinterest, showed that the shift from tools to agentic, outcome-driven AI is already underway.
Below are the most crucial takeaways shaping how we should think about AI, customer experience, and operations today and what this means for companies like Axendi.
The future belongs to those who use AI responsibly and at speed
Microsoft’s Brad Smith captured it well: there has never been a moment like this in technology.
Successful AI requires three elements:
- Technology
- Talent
- Trust
Scaling AI is no longer just about deploying tools. It’s about respecting local laws, cultures, and societal expectations. Companies that anchor AI in trust, transparent data use, explainability, and clear accountability will outpace everyone else.
And this requires determination: we must actively develop AI capabilities instead of waiting for “the right time”.
This was reinforced by leaders from Toloka AI, DefinedAI, and Lattice, who emphasized that data transparency and informed consent will define competitive advantage.
This echoes strongly with what we see at Axendi: organizations that adopt AI early, even in small steps, learn fastest, avoid steep transformations later, and gain immediate operational benefits.
Agentic AI is moving from concept to production — everywhere
Only a few months ago, “AI agents” sounded experimental. At Web Summit, one thing was clear:
AI agents are already working, millions of them, across industries, solving real tasks.
From customer service automation, to workflow orchestration in enterprise teams, to industrial robotics coordinated through digital twins, agents are becoming the invisible workforce behind business processes.
Several trends stood out:
- 80% of customer tickets resolved autonomously (Glean)
- Enterprise-grade agents coordinating each other’s work (Decagon)
- AI agents supporting education — “a professor clone that helps every student” (Superhuman)
- Industry agents training inside digital twins (Siemens, NVIDIA)
- Travel, commerce, and healthcare shifting to deeply personalized AI journeys
Alongside these examples, Atlassian offered an important perspective: AI adoption in large organizations requires a cultural shift as much as a technological one. Anu Bharadwaj emphasized that teams must treat AI as an emerging strategic capability and not a one-off initiative, and redesign workflows around continuous learning, experimentation, and augmented decision-making.
This aligns closely with enterprise realities: the companies that adapt their culture, governance, and collaboration models will gain the most from agentic AI.
We are entering the era of agentic workflows, not tools
Many speakers, including Shishir Mehrotra (Superhuman), Jesse Zeng (Decagon), Timothy Young (Jasper), Anu Bharadwaj (Atlassian), and Tao Zhang (Manus), pointed to the same shift:
AI will not replace individual products. It will replace workflows.
People will stop “using a tool” and instead rely on agents that:
- anticipate needs,
- act before being asked,
- coordinate with other systems,
- and operate continuously in the background.
This has profound implications:
The era of standalone software is ending. The era of connected autonomous agents is beginning.
Companies that still think in terms of “products” will fall behind those designing outcomes.
At Axendi we see this already: clients no longer ask for a tool. They ask for a resolution, automation of a process, or elimination of a bottleneck.
Data is the new fuel but consent is the new currency
AI leaders stressed a point often ignored in hype-driven conversations:
AI depends on data quality, legality, and permission.
Three main categories of data require careful handling:
- Public data (not always free or copyright-clear)
- Co-sourced data used for AI training
- Customer-owned data
Users must understand exactly what they consent to. This is the foundation of trust.
For companies operating in CX and BPO, this is a critical advantage: trusted handling of sensitive data becomes a competitive differentiator.
Industrial AI is no longer futuristic — it’s engineering reality
Siemens and NVIDIA demonstrated a world that once felt like science fiction:
- robots and machines that think, adapt, and create
- factories with digital twins tested virtually before physical deployment
- AI-powered industrial systems consuming massive energy (as much as Portugal today)
- simulation layers training agents in safe digital environments
Industrial AI will redefine manufacturing, logistics, energy, and urban planning.
For CX and back-office operations, it’s a signal:
industry, commerce, and customer service will be connected and optimized by agents trained in hybrid digital-physical environments.
Consumer AI will become deeply personal and deeply embedded
Speakers from Yanolja Cloud, Lighthouse, Wayflyer, TikTok, Meta, Amazon, Apple Music, Uber, bunq, Monzo, and Payable highlighted how AI will redefine consumer journeys:
Travel
Personal AI travel agents will design fully tailored trips based on your preferences, health, and lifestyle.
E-commerce
AI will cut operational costs dramatically and shift the power from platforms to agents that satisfy demand rather than generate it.
Healthcare
Wearable ecosystems (including solutions like Oura) will create predictive and preventive care journeys, supporting — not replacing — medical professionals. The goal is to keep you healthy and active before there is a need for any treatment.
Banking & Fraud Prevention
Real-time data-sharing and alerting system between institutions and businesses will be a game changer in preventing fraud and money laundering, with AI reducing noise and enabling humans to focus on complex cases.
Europe has a unique opportunity, if it acts boldly
VCs and founders agreed:
- Europe has exceptional talent
- Cultural adaptability gives it an edge
- Strong regulation can be a strength if aligned with innovation
- New AI giants will emerge from this current “bubble”
The bottleneck is not ideas. It’s the lack of engineers and strategic focus. Overregulation might be an impediment, but reasonable law focused on fair-play, trust and cybersecurity is still needed.
Companies and countries that pivot quickly and build around AI-first models will define the next decade.
Leadership lesson: cooperation will define winners
A recurring theme across the summit:
AI progress depends on collaboration between big tech, startups, regulators, and users.
No single company, not even the largest, can build the future alone.
Agentic AI requires:
- shared data strategies
- transparency
- responsible governance
- and cross-industry alignment
This mirrors Axendi’s perspective:
AI is not a “competitive wall”. It’s a collaborative layer enabling smarter, more efficient work.
What resonated with me most
After days of intense discussions with the world’s leading minds:
- AI agents are no longer theoretical. They already run production environments.
- New companies are achieving massive success in months, not years.
- Cross-industry cooperation is essential for progress.
- Industrial, medical, and robotic AI is entering sci-fi territory but grounded in real engineering.
- Human-AI collaboration, not replacement, is the universal narrative.
- Agentic AI will appear in every part of business and consumer life.
- AI might kill standalone products but will create intelligent, problem-solving systems.
- The world wants solutions to real-life problems and not more tools.
- The AI “bubble” will produce the next generation of global winners.
- Trust, data, and collaboration are the three pillars of sustainable AI development.
What this means for Axendi
Everything discussed at Web Summit aligns with our strategic direction:
- strengthening multilingual CX and BPO services
- designing outcome-based workflows
- focusing on trust, data quality, and measurable results
AI is not replacing what we do. It is amplifying our ability to deliver value, faster and at scale.
And the companies that embrace this reality early, responsibly, and with the right partners will shape the next decade of business.
