As we approach 2025, technology leaders across industries are gearing up for a rapidly evolving landscape. With AI continuing to dominate conversations and new challenges emerging in cybersecurity, infrastructure, and business operations, it’s clear that the future will require agility, foresight, and innovation.
In a recent roundup by Forbes Technology Council, leaders from various sectors shared their top predictions and strategies for navigating the tech landscape in 2025. Here’s a summary of the key challenges and insights they expect to face:
1. Driving Engineering Productivity
Challenge: In an increasingly complex tech environment, driving engineering productivity remains a top priority. Leaders are looking to leverage generative AI and intelligent automation to streamline workflows while nurturing a people-first culture to maintain creativity and speed.
Action: Companies are focusing on data-driven optimization to enhance agility, accelerate scalability, and maintain high levels of innovation. By investing in upskilling and aligning team goals, businesses can ensure their workforce remains adaptive and productive.
— Thushera Kawdawatta, Axiata Digital Labs
2. Ensuring Safety and Reliability of AI Systems
Challenge: As AI becomes more autonomous and capable of complex tasks, maintaining its safety and reliability will be crucial. AI systems will need to be transparent, predictable, and secure as they tackle increasingly sophisticated roles.
Action: AI developers are prioritizing high-quality data to ensure AI advancements are responsible, ethical, and impactful. This requires robust oversight and continual testing to prevent unintended consequences.
— Olga Megorskaya, Toloka AI
3. Navigating Funding Challenges
Challenge: With changes in the recurring revenue model and increasing competition for investment, tech leaders must adjust their strategies to maintain funding and investor confidence. Investors are placing more emphasis on long-term Monthly Recurring Revenue (MRR) and customer retention metrics.
Action: To overcome these challenges, companies are focusing on value-based pricing models and integrating advanced solutions to highlight customer value and justify long-term viability.
— Matthew Sole, Zeal
4. Leveraging AI for Compliance and Reporting
Challenge: AI’s potential to revolutionize compliance and reporting in industries like finance is growing. As regulations evolve, businesses must ensure AI tools can support accurate and efficient compliance while maintaining human oversight.
Action: Financial organizations are using AI to streamline compliance processes, automate transaction analysis, and identify potential issues. However, leaders emphasize that AI is best used as a tool to augment human decision-making, not replace it entirely.
— Naveed Anwar, Citi
5. Building Flexible Architectures
Challenge: As organizations move toward newer models, building architectures that are adaptable and flexible is a key challenge for tech teams. Businesses must future-proof their infrastructure while maintaining flexibility for emerging technologies like Generative AI.
Action: Companies are focusing on creating platforms that allow easy deployments, extensibility, and end-to-end evaluations to ensure that their infrastructure remains adaptable as new technologies emerge.
— Meghana Puvvadi, NVIDIA
6. Turning AI Into a Revenue Engine
Challenge: Companies can no longer just use AI for automation; it must become central to their revenue engine. The shift from merely using AI for tasks like customer support to embedding AI into core business functions will be crucial for growth in 2025.
Action: Leaders are working to integrate AI into every part of the business, ensuring it drives tangible value and creates new revenue streams rather than just improving efficiencies.
— Daniel Kachab, Choco
7. Protecting an Expanding Attack Surface
Challenge: As more organizations embrace AI and machine learning, their digital attack surfaces will expand, making it harder to secure sensitive data and systems. At the same time, regulatory challenges will rise due to varying privacy laws across regions.
Action: Strengthening cybersecurity protocols will require innovative solutions, including AI-powered threat detection, to protect against a growing number of cyber threats and comply with global regulations.
— Kalyan Gottipati, Citizens Financial Group, Inc.
8. Balancing Innovation with Legacy Systems Management
Challenge: Tech leaders must strike a balance between fostering rapid innovation and maintaining legacy systems. As businesses modernize, they must avoid disrupting existing workflows while adopting future-ready technologies.
Action: Many organizations are opting for hybrid solutions that allow incremental modernization of core systems without overwhelming budgets or causing significant disruptions.
— Mohit Gupta, Damco Solutions
9. Integrating AI with Containerized Infrastructure
Challenge: The integration of advanced AI systems with containerized infrastructures will be a significant hurdle for tech leaders. Ensuring seamless compatibility while optimizing for performance, security, and scalability is crucial.
Action: Companies will focus on developing container-based infrastructures that can scale AI workloads while maintaining high security and performance standards.
— Ben Ghazi, Codiac
10. Defining New AI-Powered Software Development Processes
Challenge: The shift to AI-driven software development will redefine team roles, workflows, and processes. Organizations will need to adjust their development processes to harness AI’s full potential.
Action: Businesses are already designing new development workflows, redefining roles, and integrating AI-powered collaboration tools to drive innovation and improve productivity.
— Darko Pavic, Fiscal Solutions
11. Balancing Scalability and Speed
Challenge: As customer demands become increasingly immediate, companies face the dual challenge of scaling operations rapidly while delivering high-quality, reliable solutions.
Action: Optimizing infrastructure, adopting modular architectures, and streamlining deployments will be essential to meeting fast-growing customer expectations without compromising quality.
— Cristina Gupca, Key IVR
12. Managing Transformation Across Departments
Challenge: Tech leaders in 2025 will need to manage transformation across multiple departments, not just IT. The looming SAP migration deadline will require cross-functional collaboration and alignment to ensure smooth transitions.
Action: Leaders are adopting process intelligence to improve decision-making and ensure efficient execution of migration strategies, whether they are greenfield, brownfield, or bluefield.
— Kerry Brown, Celonis
As we look toward 2025, the challenges facing tech leaders are both vast and complex. From the ethical use of AI to cybersecurity, funding challenges, and infrastructure management, the focus will be on adaptability, resilience, and proactive planning. AI, in particular, will be at the forefront, with organizations striving to unlock its full potential while ensuring safety, scalability, and alignment with broader business goals. The next few years will be pivotal for companies as they work to stay competitive in a rapidly changing technological landscape.
