Organizations at the global forefront of AI utilization – what drives success?

What have the leading organizations, who are leveraging AI with us at the forefront, included in their training programs to make the sprint in AI utilization and benefit realization possible? Behind it all is a strong leadership understanding of the scale of change and the ability to enable it, the courage to experiment, and ensuring staff competence. The benefits are visible in areas such as meaningful work, productivity, and new business opportunities.

Currently, there is an intense sprint underway to grow understanding and capabilities, preparing for the marathon ahead – the innovation opportunities that AI will offer in the future. This article dives into how every organization can get itself into peak condition.

1. Ownership, enablement, and strategy

”One of the first steps to success is taking ownership at the executive and board level. As work fundamentally changes, it must be understood that not everything a company produces can be directly translated into dividends. Agile experimentation can go a long way without major investments, but if AI adoption is only viewed through the lens of cost savings or the company as a dividend machine, you won’t succeed in competition,” comments Sulava’s Senior Consultant Mikko Torikka.

”In organizations where utilisation is advanced, leadership recognized early on that qualitative metrics such as employee well-being and meaningful work are quickly achievable. At the same time, improvements in quality, time and cost savings, and efficiency emerge. For example, in public administration, we often hear that the traditional path of cost-cutting has been exhausted. It’s time to think about how to do things differently – smarter instead of just cutting. Concrete business benefits, such as the ones in process optimization, only come through the development of agents,” adds Sulava’s Head of AI Tommi Lehmusto, and continues:

“So first, think about your own staff and how you can improve: better tools, employee experience, and meaningful work. Empower them to use AI agilely in their work. Then, by leveraging your staff’s AI capabilities, you can begin to create entirely new business, service experiences, customer value, or more time for patients for example – all thanks to AI.”

When leadership enables the foundation by giving time for adoption and innovation, providing training, and creating a framework through an AI strategy, typically several enthusiastic teams emerge within the organization to drive utilization forward.

“You get a wealth of ideas from staff by training them, using AI together in an agile way, and discussing about it. Everyone – employees and leadership alike – must find the benefits for their own work and share them with others. When an individual employee knows how to use AI, the organization’s capabilities grow,” says Lehmusto.

Another key success factor is creating an AI strategy, which brings forth steps such as technology choices, process management, data quality, governance and organization, and security. A practical AI strategy includes, for example: what we use AI for, what we want to achieve, which technologies suit our goals and environment, and how we systematically seek benefits from AI.

“If we rely on AI being just a part of the existing strategy without adjusting it, the strategy won’t be future-proof. AI has so much potential to change how things are done and what can be done. Leading organizations take this seriously. AI must be applied precisely where it adds value to the business or process,” Torikka concludes.

2. Data feeds the goodness of AI

Microsoft 365 Copilot integrates efficiently into employees’ toolkits. Organizational data is securely accessible once the initial preparations for data protection have been completed. Data, its quality, and governance are central development areas.

“Data feeds the goodness of AI, and employees must have a secure way to utilize organizational data – otherwise, AI in work use will fall short. In the Microsoft environment, it’s simple to get this right: we’ve deployed Microsoft 365 Copilot with dozens of clients in finance, healthcare, and critical infrastructure sectors, where data protection is critical. One of our strengths is that we have deep experts under one roof – from data protection to pedagogical support for staff and AI agents,” says Tommi Lehmusto.

“It’s also not worth waiting until all data is perfect and organized. Agile AI agent pilots can be made to work by limiting them to a specific part of the data. These pilots help you understand what could be done with agents and what it means for our business. That insight and understanding are an important step,” comments Sulava’s Principal Consultant, Microsoft MVP Mikko Koskinen.

3. Experimentation leads to the development of complex business solutions

Over the past year, AI agents have broken into broader awareness. AI agents, for example, handle repetitive tasks, connect systems, and automate processes. They operate autonomously or semi-autonomously, performing tasks and communicating with people or systems without constant human supervision. At Sulava, we’ve created agent solutions across various industries—from healthcare to manufacturing—ranging from smaller customer service bots to larger contract agents.

”The best dare to experiment to gain understanding. They don’t wait for someone somewhere in the world to try it perfectly. Start by enriching your team’s work and improving personal productivity in everyday tasks, and move from there toward increasingly complex business solutions—first you learn to crawl, then to walk,” comments Mikko Koskinen.

Agent development doesn’t happen solely within IT. When development is close to the business, new breakthroughs are most likely. And for development related to business processes to truly work, strong support is needed. The organizations that succeed best in leveraging AI have either heavily supported their teams or at least allowed agile development in terms of resources, and in working hours.

“Agents have significantly changed how much people understand business process development, want to engage, and eagerly experiment themselves—this scale of business-driven development hasn’t been seen before. Different roles within the organization must collaborate closely during the planning phase to ensure the solutions truly serve their purpose,” Koskinen concludes.

4. Courage, curiosity, and collaboration

Working with hundreds of customers, our experts have found that coaching through the customer organization’s own use cases and teams is the most effective way to learn. Typically, teams first discover small areas for improvement in their daily work with the help of AI, which then leads to larger innovations.

“If the employee doesn’t understand, nothing changes. Technically initiated pilots—of which there are currently thousands underway in Finland—are designed to test the platform’s technical functionality. From there, AI adoption must be deeply integrated into employees’ work and the business itself.

”When both individuals and organizations have courage and curiosity, and new things are embraced through close collaboration and shared experiences, the marathon of work transformation runs smoothly,” concludes Mikko Torikka.

Sulava named winner of the 2025 Microsoft Copilot & Agent Partner of the Year Award

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