ALTEN Group

Gualtiero Bazzana

Technology has shaped every stage of Gualtiero Bazzana's career, but one principle has remained constant: innovation matters only when it delivers measurable business value.

From building companies as a young entrepreneur to serving two terms as worldwide President of the International Software Testing Qualifications Board (ISTQB) and contributing to the Alten Group in multiple Business Roles (Managing Director and P&L responsible for several multinational perimeters involving as well several M&A finalization and integration) and since 2024 as CAIO - Chief AI Officer, he has consistently approached technological change through the lens of engineering discipline, customer responsibility and business outcomes.

That philosophy now underpins how ALTEN’s CAIO is leading AI across one of the world's largest engineering and technology consulting organizations.

"In terms of management, AI is no different from other technologies having a strong impact on business transformation. It requires technology, governance, organization, a clear strategy and constancy of purpose," says Gualtiero.

Rather than pursuing AI for its own sake, he believes organizations must build the foundations that allow intelligence to become a trusted, scalable and measurable business capability.

The foundations of that thinking were established long before AI entered the boardroom. Building and scaling businesses taught Gualtiero that technology succeeds only when it solves real customer challenges and strengthens commercial performance. His technical and business background reinforced an engineering mindset that values rigor, quality and accountability in every technology initiative. Together, those experiences continue to shape how AI is managed at ALTEN, balancing innovation with disciplined execution as the company scales AI across its global operations.

The years leading the International Software Testing Qualifications Board (ISTQB) further strengthened that perspective. Working across more than one hundred countries exposed him to different regulatory environments, business cultures and operating models, reinforcing his belief that successful global programs require a consistent strategy while adapting to local regulations, business practices and cultural realities.

Building AI around Business Outcomes

When the AI program was launched at ALTEN, the strategy was not to launch isolated innovation projects but a coordinated program capable of creating value across the business. That vision became the “AI At ALTEN (A3)” global AI program.

Rather than organizing AI around technologies, A3 has been built around three business priorities. The first strengthens customer engagement, develops new business opportunities and supports strategic partnerships. The second applies AI directly to engineering projects, improving productivity, delivery quality and operational efficiency while delivering stronger customer outcomes. The third integrates AI into corporate functions including finance, recruitment, human resources and other internal operations to improve organizational efficiency.

Collectively, the three pillars are designed to strengthen revenue growth, improve project profitability and increase operational efficiency, aligning AI investment directly with the company's overall financial performance.

Among A3 three pillars, AI for Project Performance has delivered the strongest momentum. Instead of limiting AI to pilots, ALTEN embeds it directly into live engineering engagements across software development and code modernization, testing, product design, quality engineering, manufacturing, supply chain and technology consulting. Working within real customer projects allows teams to improve delivery while gaining hands-on experience with AI in production environments.

In accordance with collected feedback and metrics, the benefits extend beyond productivity. Embedding AI into ongoing engagements creates closer operational partnerships with customers while providing practical experience with AI in real customers’ environments. Having deployed this approach across more than a thousand engineering activities, it has become one of ALTEN's most effective ways of demonstrating AI's business value while strengthening long-term customer relationships.

Governance before Scale

While innovation often dominates AI discussions, ALTEN believes governance determines whether organizations can scale successfully. Leading AI across a multinational organization requires balancing centralized direction with local execution. ALTEN has established a central AI organization responsible for strategy, governance, priorities and common standards across the Group. Supporting that team is a network of AI Ambassadors embedded within each legal entity and working closely with local leadership.

Their role flows in both directions. They adapt global initiatives to regional regulations, customer requirements and market conditions while bringing local priorities back into the central roadmap. The structure reflects a leadership philosophy Bazzana has carried throughout his career, one that recognizes sustainable global programs depend as much on local ownership as they do on centralized strategy.

Governance also extends beyond organizational design. ALTEN has implemented an AI Management System designed around the European AI Act and ISO 42001 principles, with the organization preparing for ISO 42001 certification. Alongside investments in AI platforms, workforce upskilling, internal communication and reusable engineering assets, these foundations enable AI to become a trusted enterprise capability that customers can adopt with confidence.

" AI is a technology with a heavy impact on business transformation. As such, it requires technology, governance, organization, a clear strategy, and constancy of purpose. "

The AI training program is an important part of A3, with more than 60 percent of engineers having already been upskilled through the ALTEN AI Academy, with a target to cover all employees within a short time.

Technology with Purpose, Not Preference

As AI technologies evolve rapidly, Gualtiero believes organizations must avoid becoming tied to a single technology ecosystem. For a global engineering consultancy like ALTEN, whose customers operate across different cloud platforms, language models and infrastructure environments, flexibility is essential.

That philosophy has shaped ALTEN's multi-partner strategy. Rather than promoting one platform over another, the company builds expertise across multiple technologies so it can support customers based on their existing technology choices and business objectives: serving customers effectively means adapting to their environments, not asking them to adapt to yours.

Within this strategy, ALTEN's partnership with Mistral has become particularly valuable because its engineering heritage and deployment flexibility closely align with ALTEN's industrial customer base. Moreover, strategic autonomy represents a fundamental asset for large European organizations, and in this sense ALTEN also uses Mistral's technology internally, enabling engineers to build practical expertise before applying it within client engagements. This combination strengthens both technical capability and credibility while remaining part of a broader technology ecosystem.

People Drive Scale

Technology alone does not determine whether AI succeeds across an enterprise. People do. One milestone ALTEN’s CAIO is particularly proud of is making AI tools available to every ALTEN employee, tailored to individual roles. While the organization expected gradual adoption, engineers embraced the technology far more quickly than anticipated, moving rapidly from basic prompt engineering to retrieval-augmented generation and increasingly agentic workflows.

The experience reinforced ALTEN’s belief that governance, training, and accessible technology together make adoption a natural outcome. The challenge is no longer convincing employees to use AI but continuing to deliver new capabilities at the pace they expect, within a governance framework ensuring compliance at all levels.

Engineering and Ensuring the Quality of the Next Generation of Intelligent Systems

When it comes to Engineering the Next Generation of Intelligent Systems, it is important on one side to reduce the technical debt through AI-driven code modernization and on the other to implement new applications with a completely new set of tools, processes and skills.

At ALTEN, AI-driven offers have quickly become the ”New Normal” with close to 80 percent of our proposals embedding AI solutions or features at various levels, not for the sake of AI but as a means to improve our engineering services and deliver more value to our customers.

But engineering is not limited to requirements engineering, design and development: it must also involve a significant level of testing, especially for business critical applications – that are the focus of ALTEN in sectors like aerospace & defense, energy, transportation (automobile, railway, naval), telecommunications & media, financial services, retail and public administration.

Bazzana's long involvement in software quality also shapes how he views the future of AI applications. He believes AI is transforming testing in two ways.

The first is by improving traditional testing through automated test generation, better traceability, script adaptation and more comprehensive regression testing. These capabilities improve both software quality and productivity up to 35 percent.

The second transformation is more fundamental. AI-enabled systems cannot be validated using the same assumptions as conventional software because their behavior depends on evolving models, probabilistic outputs and evolving technologies. Testing AI systems therefore requires methodologies specifically designed for AI rather than extensions of traditional software testing.

Drawing on both his responsibilities at ALTEN and his continued involvement with ISTQB, Gualtiero Bazzana sees this as one of the next major disciplines in software engineering as AI becomes increasingly embedded within products and services.

Measuring What Matters

Looking ahead, ALTEN believes the greatest challenge is no longer building AI systems but governing them responsibly at scale. As organizations move toward agentic AI, success will depend on observability, traceability, orchestration, compliance and operational control. Without those foundations, scaling autonomous systems will become increasingly difficult.

ALTEN sees enterprise AI progressing through three stages: enhancing individual productivity, redesigning business processes and embedding AI directly into products and services. It is this final stage, where AI becomes part of what organizations deliver rather than simply how they work, that will create the greatest long-term value.

For an engineering consultancy like ALTEN, that evolution represents more than adopting another digital technology. It reflects a fundamental shift in how engineering solutions are designed, developed and delivered, with AI becoming an integral part of both the engineering process and the products created for customers.

For ALTEN, however, the clearest indicator of AI maturity is not adoption but business performance. Early in an AI journey, organizations naturally measure adoption metrics to understand whether the foundations are in place. As programs mature, those “vanity metrics” become less meaningful. The focus should shift to business KPIs that demonstrate whether AI contributes to revenue growth, project performance, profitability, customer relationships and competitive advantage, supported by disciplined execution, responsible governance, and clear business accountability.

At ALTEN, the A3 program is managed at ExCom level, with a strong involvement of the Chairman of the Board, the CEO, as well as the CFO, CIO and the EVP of the various business perimeters, and thus it is normal that AI becomes part of the business rather than remaining a technology initiative.

As AI continues to reshape engineering, ALTEN remains focused on the responsibilities that come with leading its adoption: success will not be defined by how quickly organizations embrace new technologies, but by how effectively they integrate them into their business, empower their people, strengthen customer outcomes and build systems that can be trusted at scale.