Staying on top of emerging tools and trends is all in a day’s work for tech leaders across industries. Tasked with preparing their organizations to be ready for new developments and regulations, as well as with driving the evolution of their companies’ tech stacks, it’s vital for tech leaders to always have one eye on the present and another on what’s coming down the road.

As they look ahead to 2025, many tech leaders see a continued focus on the optimal and ethical use of artificial intelligence, but AI is far from the only topic of conversation. Below, members of Forbes Technology Council detail the specific challenges they expect to be tackling in 2025 as well as what they, and their organizations, are doing to prepare.

1. Driving Engineering Productivity

Driving engineering productivity amid a complex tech landscape will be a challenge. We’re tackling this by leveraging generative AI for intelligent automation, building accelerators for speed and scalability and fostering a people-first culture. By igniting passion, upskilling talent and aligning goals, we ensure innovation thrives. Data-driven optimization keeps processes agile and impactful. – Thushera Kawdawatta, Axiata Digital Labs

2. Ensuring The Safety And Reliability Of AI Systems

As AI advances in reasoning, autonomy and domain expertise, 2025 will see it tackling complex tasks and driving automation. The challenge will be ensuring safety and reliability as systems grow more complex. My team is dedicated to providing large language model developers with top-quality data to support the safe, responsible and impactful advancement of these technologies. – Olga Megorskaya, Toloka AI

Monthly recurring revenue value is changing, with investors looking for long-term evidence of MRR to indicate a business’s viability in an increasingly competitive market. This change will lead to tech leaders facing funding challenges in the coming years. For us, value-based pricing models and integrations are now integral to showcasing long-term customer value as we adapt to this evolving culture. – Matthew Sole, Zeal

4. Leveraging AI For Compliance And Reporting

In 2025, AI tools could potentially support treasury and finance teams in ensuring compliance with regulations and reporting requirements by analyzing transactions and identifying potential compliance breaches. However, we must all keep in mind that human intelligence cannot be replaced by machines, and AI is best viewed as a tool to drive greater productivity and free time for higher-order work. – Naveed Anwar, Citi

5. Building Flexible Architectures

One of the biggest challenges for leaders and teams in enterprises will be building architectures that are flexible and can adapt to newer models, prompting strategies, guardrails and tools. My organization is focusing on building platforms that enable architectural flexibility and extensibility, easy deployments, and thorough end-to-end evaluations while incorporating evolving patterns of GenAI. – Meghana Puvvadi, NVIDIA

6. Turning AI Into A Revenue Engine

Every company has to become AI-first—AI has to become their revenue engine. It is not enough to just automate processes, such as customer support, with AI. This is the bare minimum. Companies have to get AI into their core. – Daniel Kachab, Choco

7. Protecting An Ever-Expanding Attack Surface

Cybersecurity and data privacy are highly interconnected. As organizations increasingly rely on AI and machine learning for decision making and operations, the attack surface for cyberthreats will expand, making it more difficult to secure sensitive data. Moreover, growing demand for cross-border data flows will create complex regulatory challenges, especially with varying privacy laws across regions. – Kalyan Gottipati, Citizens Financial Group, Inc.

8. Balancing Rapid Innovation With Legacy Systems Management

Tech leaders in 2025 will face the challenge of balancing rapid innovation with managing legacy systems. Our focus will be on adopting hybrid solutions that modernize core operations incrementally while integrating scalable, future-ready technologies. This ensures continuity without disrupting workflows or overwhelming budgets. – Mohit Gupta, Damco Solutions

9. Integrating Advanced AI With A Containerized Infrastructure

In 2025, tech leaders will face the dual challenge of integrating advanced AI systems while optimizing containerized infrastructure for these AI workloads. Success will hinge on embracing this container-centric, AI-powered approach by creating flexible, container-based infrastructures that can seamlessly integrate emerging AI technologies with high security, scalability and performance. – Ben Ghazi, Codiac

10. Defining New AI-Powered Software Development Processes

2025 will be a transformative year for tech as AI reshapes how we work. AI-driven software development promises huge benefits, but achieving them requires evolving team roles and workflows. At our company, we’re already designing a new development process, redefining roles and embracing innovation to lead the future of AI-powered collaboration. It’s an exciting journey ahead! – Darko Pavic, Fiscal Solutions

11. Balancing Scalability And Speed

A key challenge will be balancing scalability and speed as customer demands grow increasingly immediate. Everyone wants solutions “yesterday,” driven by fast-evolving technology, rising expectations and shifting regulations. We’re optimizing infrastructure, adopting modular architectures and streamlining deployments to deliver fast, reliable solutions without compromising quality. – Cristina Gupca, Key IVR

12. Managing Transformation Across Departments

In 2025, tech leaders will be faced with managing transformation efforts that touch and require engagement from every department, not just IT-focused activities. With the looming 2027 SAP migration deadline, process intelligence will accelerate smarter selection and execution of “greenfield,” “brownfield” and “bluefield” migration strategies. – Kerry Brown, Celonis

13. Finding Engineers With AI And Data Analysis Skills

One big challenge tech leaders will face in 2025 is the shortage of engineers who excel at AI foundations and embrace data complexity. To address this, our team plans to invest in upskilling current employees, partnering with educational institutions and leveraging AI developer tools like Copilot to improve productivity while keeping data at the forefront of decision making. – Akshay Prabhu, Capital One

14. Scaling AI While Maintaining Quality And Compliance

In 2025, the challenge will lie in scaling AI without compromising quality or compliance. Human-in-the-loop workflows will be vital for bridging the gap between AI efficiency and the nuanced understanding humans bring. This collaboration ensures accountability, reduces bias and adapts systems to meet evolving ethical and regulatory demands, building trust in AI as it becomes more pervasive. – Michael Malyuk, HumanSignal, Inc.

15. Managing Rapid Innovation Ahead Of Regulatory Guidance

A key challenge for tech leaders will be managing rapid innovation that outpaces regulatory frameworks. As AI and Web3 technologies evolve, traditional regulations lag behind. By embedding compliance as a real-time checkpoint in workflows, teams can stay agile, adapting to new rules as they emerge. This approach ensures innovation moves forward without losing focus on legal essentials. – Sheraz Ahmed, STORM Partners

16. Ensuring Smooth Collaboration Between Human Workers And AI Agents

The rapid adoption of agentic AI models will pose significant organizational and leadership challenges. Leaders will need to begin exploring the concept of collaboratively managing their carbon-base workforce (humans) and their silicon-base workforce (AI agents). They will also need to determine the appropriate operating model and structural changes to maximize the benefits of these investments. – Mark Cameron, Alyve Consulting

17. Addressing AI-Enhanced System Attacks

AI-enhanced attacks will increasingly target machine identities and service accounts in 2025. To address this, enterprises need AI-driven identity security that continuously discovers vulnerabilities, assesses emerging risks and automatically adjusts access controls, fundamentally improving the protection of an expanding nonhuman identity landscape. – Tim Eades, Anetac

18. Fully Embracing DevSecOps

Tech teams will fully embrace DevSecOps as a transformation rather than a set of point solutions. This will align security and development processes within a risk-management framework so teams can work toward shared goals without disrupting existing workflows. To get started, we’re advocating an incremental approach, building targeted use cases that showcase the hard ROI of integrated security. – Brittany Greenfield, Wabbi

19. Updating The Software User Experience

With AI, the UX field has made a giant leap forward in delivering value without friction. Where before we had search, filter and nested navigational menus, we now have the ability to speak to software, be understood and get what we need when we need it. This leads us to reconsider our own software systems and work to improve internal and external tooling. – Lindsey Witmer Collins, WLCM “Welcome” App Studio

20. Orchestrating Safe, Ethical Enterprise-Scale GenAI

Looking ahead to 2025, the paramount challenge will be orchestrating enterprise-scale generative AI while fortifying security and ethical governance. We’re executing a strategic framework of robust governance protocols, scalable implementation paradigms and sophisticated monitoring systems, accelerating innovation while maintaining uncompromising security standards. – Hrishikesh Joshi, Okta Inc.