IT Nation Connect™ Europe 2026 reflected the growing momentum across the MSP industry as providers prepare for the next phase of AI-driven service delivery.
AI is rapidly reshaping how managed services are delivered. During the opening keynote Manny Rivelo, CEO of ConnectWise, delivered a blunt reality: “The MSP of today will not exist in just a few years.”
In the AI era, the providers that thrive will be those who turn automation and operational data into action.
Across keynotes, partner panels, and breakout sessions, three shifts consistently emerged as the foundation for the next generation of MSP success:
These shifts are pushing the industry toward a new model of autonomous service delivery. The question for MSP leaders is whether they can transform their operations fast enough to remain competitive in an AI-driven industry.
The reason for these shifts becomes clear when you look at the pressures redefining the MSP business model and the opportunity to lead in the age of agentic AI by scaling service delivery more efficiently without proportional headcount growth.
During the welcome keynote at IT Nation Connect™ Europe 2026, Manny Rivelo highlighted a defining challenge for the managed services industry: demand for IT services is growing faster than the traditional MSP operating model can scale.
One of the biggest pressures comes from the MSP cost structure itself. Labor typically represents 75–85% of cost of goods sold (COGS) for managed services. As wage pressures continue and service expectations rise, adding headcount at the same pace as the business is becoming increasingly unsustainable.
At the same time, there’s a surge in AI investment. Global AI spending is growing roughly 44% year over year, accelerating innovation across service management, monitoring, cybersecurity, and automation solutions.
For MSPs, the impact is already visible. AI-powered capabilities are beginning to automate routine tasks, streamline service delivery workflows, and assist technicians with faster troubleshooting and remediation. Instead of scaling purely through headcount, MSPs can increasingly leverage agentic AI and intelligent automation to expand capacity.
This shift is changing the formula for success. AI is more than a technology trend. It is becoming a business lever for scalable, sustainable growth, enabling MSPs to deliver better outcomes for customers while maintaining healthy margins.
For AI to deliver on the promise of helping MSPs scale services more efficiently, it must be built on a strong operational foundation. For years, core tools such as PSA, RMM, and documentation have served primarily as systems of record, i.e., repositories for tickets, device data, configurations, and operational history.
In this model, systems capture what happened, but technicians still have to interpret the information and decide what action to take next.
But adding AI on top of fragmented tools or inconsistent data will not deliver meaningful results. Without context and structured operational information, AI lacks the signals it needs to reliably interpret events or automate workflows.
That is why the conversation is shifting from systems of record to systems of action.
Instead of just storing information or generating insights, systems of action are designed to interpret operational signals and automatically execute the next step. AI can analyze alerts, tickets, and telemetry, determine the appropriate response, and trigger remediation workflows, resolving issues or advancing service tasks without waiting for manual intervention.
At the center of this shift is data. ConnectWise leaders often describe data as “the oxygen for AI,” underscoring its importance in AI implementation.
The richer and more structured the operational data inside MSP tools (ticket history, asset data, alerts, workflows, and documentation), the more powerful AI capabilities become. When AI can continuously learn from this data, it enables smarter automation, faster troubleshooting, and more proactive service delivery.
“A common mistake we see is MSPs with data sprawl and disparate tools. The more unified your data is, the better outcomes you’ll get from AI. Even small things like cleaning up how customer names are structured in your PSA can have a massive downstream impact on AI outcomes.”
Lee Silverstone, SVP, AI Platform, ConnectWise and Co-founder of zofiQ
For MSPs, the opportunity is significant: Layering AI on top of core operational systems can transform existing data into automated actions that resolve routine issues, accelerate resolution times, and scale service delivery without proportionally increasing technician workload.
If the future of managed services depends on turning operational data into intelligent action, the question becomes clear: what platform makes that possible?
During the product keynote, David Raissipour, Chief Product and Technology Officer at ConnectWise, shared how the ConnectWise Platform is designed to help MSPs succeed in an AI-first world.
With a unified platform architecture as the foundation and security-first solutions at its core, ConnectWise integrates AI-driven automation as a powerful layer on top, helping MSPs move beyond reactive IT management toward a model in which systems proactively detect, resolve, and prevent issues. By bringing operational data and workflows together, the ConnectWise Platform enables stronger automation, better visibility, and the shared context required for AI to deliver meaningful outcomes.
Several innovations highlighted during the keynote are designed to help MSPs make the transformation to autonomous service delivery while improving operational efficiency:
These innovations move MSP tooling beyond traditional systems of record, capturing alerts and events only, toward systems of action that help teams interpret signals, prioritize work, and respond faster, bringing the industry closer to autonomous service delivery.
The final keynote shifted the focus to a different but equally important factor: leadership mindset. While technology enables transformation, people and culture determine whether organizations can successfully adapt to it.
Jake Humphrey and Professor Damian Hughes, hosts of The High Performance Podcast, explored what separates high performers from the rest and the leadership mindset needed to survive and thrive in an AI-first world. Drawing from more than 450 interviews with world-class athletes, scientists, entrepreneurs, and leaders, they shared five lessons about performance, resilience, and leadership.
The lesson from Mo Gawdat, former Chief Business Officer at Google X, was that according to research, the physical stress response triggered by a negative event lasts roughly ninety seconds. What prolongs it is replaying the event repeatedly in our minds.
High performers practice “the pause,” creating space between stimulus and response so they can react with clarity rather than emotion.
For leaders managing teams and clients, this ability to pause and respond with clarity can make a significant difference in how challenges are handled.
Another lesson they shared comes from Usain Bolt’s coach, who explained that learning to lose is part of learning to win. Every setback creates an opportunity to ask a simple question: “What can I take from this that makes me better next time?”
For MSP leaders navigating rapid changes in AI, automation, and service delivery, this mindset is critical. Teams that treat failure as learning will adapt far faster than those that fear making mistakes.
Another lesson came from physicist Professor Brian Cox. Scientists spend much of their time being wrong, but that is precisely how progress is made. Each incorrect assumption reveals the limits of current knowledge and opens the door to learning. Scientists spend much of their time being wrong, but that is precisely how progress is made. Each incorrect assumption reveals the limits of current knowledge and opens the door to learning.
High-performing leaders apply the same principle. Instead of defending existing beliefs, they remain curious. They surround themselves with people who challenge their thinking and bring different perspectives.
Drawing on Formula One examples, mistakes in high-performing environments are rarely treated as individual failures. If a process breaks down, the question becomes: “How can the system be improved so the same issue does not happen again?”
This mindset builds trust within teams and encourages experimentation, both of which are essential in an industry evolving as quickly as managed services.
Across many of their interviews, Humphrey and Hughes have observed that high performers are not defined by constant success but by their ability to recover, adapt, and keep moving forward.
For example, Dame Stephanie Shirley, a Kindertransport refugee during WWII, went on to found one of the first software companies in the UK. She built groundbreaking technology in a male-dominated industry and pioneered remote work for women and people with disabilities at a time when such practices were virtually unheard of in the 1960s.
Leaders can either reflect the mood around them or change it, like a thermostat rather than a thermometer. For MSP leaders navigating rapid technological change, that mindset can shape how confidently their organizations embrace transformation.
As Manny Rivelo emphasized in his opening keynote, the MSP of today will not exist in just a few years. The providers that thrive will be those that combine AI-powered platforms, operational discipline, and leadership teams ready to adapt and innovate. AI is quickly reshaping the MSP industry, but ultimately, it’s the people leading the transformation who will turn that potential into real outcomes for their businesses and customers.
Share:
The most common risks include devices with default credentials, unpatched firmware, insecure APIs, and shadow IoT devices introduced without IT approval. These create blind spots that attackers can exploit for lateral movement, ransomware deployment, or data exfiltration.
MSPs can use continuous discovery through RMM solutions, such as ConnectWise RMM, to inventory devices in real time. Pairing this with SIEM tools, such as ConnectWise SIEM, provides visibility into device activity and integrates alerts into SOC workflows.
Zero trust ensures that every IoT device is treated as untrusted until proven otherwise. This approach enforces device identity, authentication, and least privilege access, preventing IoT endpoints from being used as backdoors into critical systems.
NIST, ISO/IEC 27001, HIPAA, and PCI DSS all expect IoT security measures, such as strong authentication, encryption, logging, and patch management. Emerging regulations, such as the US IoT Cybersecurity Improvement Act and the EU Cyber Resilience Act, are raising the baseline for IoT security standards.
RMM tools, such as ConnectWise RMM, extend monitoring and patch management to IoT endpoints, while XDR services, such as ConnectWise MDR, correlate IoT events with broader infrastructure telemetry. Together, they improve detection, streamline response, and reduce operational overhead.
