CGI Execs Advise on AI Trust and Transformation Challenges
UK businesses are falling behind global peers when it comes to AI adoption, according to research from CGI, the Canadian IT consulting and systems integration firm.
The company’s Voice of Our Clients 2025 report finds that just 21% of UK firms have achieved advanced AI implementation compared with 35% worldwide, with 63% pointing to legacy systems as the main culprit holding them back.
Talent shortages are creating additional headwinds for organisations trying to modernise operations and scale AI responsibly.
To understand what’s driving these issues and how companies can navigate them, two CGI executives provide insight.
Tara McGeehan has been President of CGI in the UK and Australia since 2019, overseeing business operations for around 8,000 technology specialists across both markets.
Her team tackles some of the region’s most complex digital programmes, giving her a front-row seat to the modernisation challenges facing large organisations.
“We’re currently delivering some of the country’s most complex and mission-critical programmes, such as our work in building and operating the Data Communications Company’s data systems for the UK’s smart meters,” she says.
Russell Goodenough, CGI’s Head of AI, brings a different perspective shaped by over 30 years delivering technology solutions to public and private sector clients.
His engineering background informs his approach to helping businesses navigate digital transformation journeys, particularly as AI accelerates the pace of change.
“The tech industry is always evolving and changing, but through AI the race has stepped up several gears all at once. This is fascinating to me, especially when it comes to finding ways for the technologies to improve society,” he says.
Together, they’re grappling with questions that extend beyond simple technology deployment: How do businesses build trust in AI systems, prepare for disruptive technologies like quantum computing – and create sustainable modernisation strategies when the underlying infrastructure is decades old?
What role does CGI play in AI and IT?
Russell: For more than two decades, CGI has delivered AI and intelligent automation as part of our end-to-end services, applying lessons learned and continuously investing in both technology and expertise.
We work with clients who want to move from experimenting with AI to putting it into practice responsibly.
Together, we focus on testing and training models securely and efficiently, often through real industry use cases that draw on our own IP solutions.
We apply our Responsible Use of AI framework, both in our own IP and in client projects, to help establish solid foundations for trustworthy and ethical AI.
Alongside this, we collaborate with a broad network of partners in AI, automation, cloud and other digital technologies to identify and implement the solutions that best fit each client’s needs.
What strategic steps should organisations prioritise now to accelerate effective AI adoption?
Russell: UK businesses are performing below global businesses when it comes to AI adoption – around 21% in the UK report advanced adoption, compared to 35% globally.
To accelerate the adoption of AI, organisations should focus on people and change as much as the technology itself.
Building trust through clear governance, transparency and leadership is just as important as technical integration.
Senior executives must champion adoption visibly, being a role-model for using AI at work, setting direction and showing how AI aligns with long-term strategy.
Practical steps include phased rollouts, hands-on training and creating AI champions across the entire organisation.
This approach builds confidence, sparks innovation for new use cases and makes adoption part of daily work, rather than a top-down directive.
How can businesses overcome the significant talent shortage, especially in the public sector, to sustain their AI and digital transformation efforts?
Russell: The challenge isn’t just a lack of people with suitable skills, it’s the sheer pace of technological change.
Public sector organisations, in particular, can struggle to keep up with new capabilities while competing with the private sector for scarce talent.
To bridge the gap, businesses need to understand three important strategies, alongside two key leadership commitments:
Making AI a part of everyday work – not through training alone, but by providing employees with hands-on opportunities to use AI tools in their roles.
This dramatically reduces the change management hurdles that can arise when implementing wider adoption.
Establishing peer networks and appointing champions who can share practical experience.
This creates a supportive environment where colleagues feel encouraged to explore AI responsibly.
Collaborating with external partners and forming diverse internal adoption teams that blend business process and technology expertise means that it’s easier for employees to understand how to apply AI to a specific task.
It’s crucial for leaders, whether senior civil servants or business heads, to visibly use and advocate for AI. When leaders role model AI adoption, it normalises experimentation and reassures teams.
Finally, leaders must allow their teams time for self-led learning. By normalising continuous learning, you create a culture where adapting to this rapidly changing new technology becomes routine.
How is CGI advising boards to prepare for emerging technologies like quantum and neuromorphic computing alongside AI?
Tara: Neuromorphic computing and quantum are illustrative of where technology is heading.
Executive boards need to prepare for these emerging technologies in the same way they have for AI – by focusing on governance, resilience and clear digital strategies.
By building strong operational foundations first, businesses future proof themselves for safe, responsible and effective adoption.
This means planning ahead, maintaining visibility over the technology ecosystem, anticipating disruption wherever possible and investing in the right tools and partners.
In addition to this, it is equally important for businesses to empower its workforce by creating opportunities for upskilling and encouraging responsible experimentation. This strengthens both trust and long-term resilience for businesses and the communities they serve.
What role do managed-service-partnerships (MSPs) and cloud migration play in helping firms modernise legacy systems that are currently bottlenecks for innovation?
Tara: Legacy technology is a significant bottleneck that can limit competitiveness and seriously hinder business performance. 63% of UK executives cite this as a serious concern.
Managed-service-partnerships and cloud migration provide a strategic route to modernisation, helping organisations build agility and resilience while managing compliance, cost and risk.
The real value of MSPs lies in continuous improvement. They ensure IT systems evolve in line with business needs, balancing ROI with long-term resilience.
By taking ownership of day-to-day management of various business systems, MSPs also free internal teams to focus on innovation, growth and the delivery of business outcomes.
In this way, MSPs act not just as technology partners but as enablers of transformation, giving organisations the foundations they need to innovate with confidence and future-proof their operations.
With concerns over online misinformation impacting business outlooks more in the UK than globally, how should technology leaders incorporate digital trust and security into their AI strategies?
Russell: Misinformation is a growing external challenge for UK businesses, with 24% of leaders in our research noting challenges in resolving this. This makes digital trust and security central to any AI strategy. It is not enough to govern internal models responsibly.
Leaders must also consider how misinformation in the wider digital environment can impact reputation and confidence.
A key risk lies in the data AI is trained on. If misinformation feeds into a model, it undermines the integrity of the entire system.
Robust governance, strong data quality controls and explainability must therefore sit alongside cybersecurity and protection measures.
By embedding accountability and trust at board level, organisations can reassure stakeholders that AI is being used safely. Digital trust is not just compliance – it is the foundation for resilience, innovation and long-term growth.