This year, I’m committed to ensuring our engineering and development teams can increase the amount of time they spend on strategic work by integrating AI into their workflows.
Tech leaders must understand and balance the risks of AI while upskilling teams to take advantage of the technology. Optimising at an individual level is great, but optimising at the team level is even better.
Last year was a pivotal point in this journey. Once perceived as a potential threat to jobs, AI technology is increasingly seen as a tool that enables workers to focus on higher-level, critical-thinking tasks that only humans can effectively execute.
I have challenged my team to understand how they can engage with AI tools to unlock efficiencies and improve productivity. For example, in software development, AI can suggest or autocomplete code and perform security testing – these are vital tasks, but they can take developers’ focus away from critical thinking and creative innovation.
AI implementation requires a community of support, teamwork and group problem-solving. To succeed, we’ll need to foster a collaborative environment where our teams can learn new skills together, expand their technical expertise and advance their career development. Over the next year, I hope all organisations can achieve sustainable and measurable returns with AI, develop frameworks to manage risk and support opportunities for teams to focus on higher-value projects.
As we enter 2025, my focus in on how to derive value from the AI investments we’ve made in the past year. My priority is to ensure we enable both our internal teams and customers to get the most from their work with the support of AI.
There have been notable advancements in AI agents and we have invested heavily in this technology. But success in getting AI agents to work as teammates with humans will hinge on data quality and trust.
An integral part of my resolutions for 2025 will be ensuring that AI has access to the most accurate and relevant information to empower our teams and customers to trust AI as they would their colleagues. Building and maintaining this trust is critical to the success of these initiatives and for achieving peak employee engagement.
Last but not least, I will continue to partner closely on influencing company and business strategy through AI and technology leadership. As tech leaders, we cannot be siloed away from our go-to-market, administrative and R&D colleagues – our work is too interdependent. With these initiatives around AI taking off, communicating and understanding employee sentiment across the business will be vital for improving and evolving as we move through 2025.
In 2025, we’re committed to taking proactive steps to help security teams accurately anticipate and predict risks and threat activity across an expanding attack surface. Integrating security operations with business-continuity planning will become essential for organisations, as it ensures security measures are aligned with the overall business strategy to maintain operational resilience.
As businesses break down data silos and accelerate their AI integration, they will need sophisticated, AI-driven security strategies. We’re committed to further developing our Vision One Cyber Security platform by leveraging AI-driven threat intelligence to enhance the detection, analysis and mitigation of cyber threats.
In 2025, we’re also aiming to expand what we call our ‘radial web’ organisational setup. This approach, which we adopted a few years ago, is aimed at creating a flatter organisation, with fewer silos, that is responsive to change. Central to this approach is our strong emphasis on internal knowledge-sharing, collaboration and mentorships.
In terms of talent and skills, we’ll invest in training and certification programmes and focus on fostering a diverse and inclusive workforce. We’ll also prioritise policies that support a healthy work/life balance. These actions will help ensure we are attracting top global talent and that our people remain motivated.
The main focus for Suse in 2025 is observability. We are working with partners and open-source communities to make data actionable, context-driven and universally accessible. The result will be improved resilience, faster innovation and more seamless integration of observability into daily engineering workflows.
We expect to see major areas where observability will considerably accelerate business success. The further commercial adoption of OpenTelemetry, as the standard for telemetry data collection, will simplify integration and enable easier adoption of observability practices, including tailored solutions.
The integration of AI and OpenTelemetry with emerging software-development kits will provide observability for applications, machine-learning models, databases and GPUs, making insights into model optimisation, prompt engineering and workload placement more accessible. Topology-based context will be critical for understanding and optimising complex AI workflows.
This year, I’m committed to ensuring our engineering and development teams can increase the amount of time they spend on strategic work by integrating AI into their workflows.
Tech leaders must understand and balance the risks of AI while upskilling teams to take advantage of the technology. Optimising at an individual level is great, but optimising at the team level is even better.
Last year was a pivotal point in this journey. Once perceived as a potential threat to jobs, AI technology is increasingly seen as a tool that enables workers to focus on higher-level, critical-thinking tasks that only humans can effectively execute.