Forrester research released many predictions for 2025. Sharyn Leaver, chief research officer at Forrester wrote a blog post to elaborate on the predictions. 

Here is an excerpt from the blog post, “2025 will be about the pursuit of near-term, bottom-line gains while competing for declining consumer loyalty and digital-first business buyers. Some leaders will pursue that goal strategically, in ways that set up their organizations for long-term success. Others won’t — and will come up against the limits of quick fixes.”

IT executives expect IT budgets to increase for 2025 and smart IT leaders will make the most of this increase. They will use it to streamline operations and upgrade the infrastructure as well as prepare their employees for emerging technologies such as generative AI. In this article, you will learn how companies can shift their AI goals for 2025 without worrying about roadblocks.

How Companies Must Shift AI Goals To Minimize Setbacks?

Here are some of the ways in which companies can shift their AI goals for 2025 without worrying about setbacks.

1. Prioritize Long-Term ROI Over Immediate AI Wins

In 2025, Forrester warns that enterprises overly focused on immediate return on investment will likely scale back artificial intelligence efforts prematurely. Many organizations pursued artificial intelligence for quick returns but sustainable growth demands balancing short-term wins with strategic foresight is crucial for success.

For artificial intelligence initiatives to succeed, companies should:

•  Focus on differentiating use cases that align with long-term business goals.

• Shift away from rapid returns and adopt a patient approach to artificial intelligence investments.

• Integrate a comprehensive data management strategy to maximize artificial intelligence’s potential value.

For organizations that step back from quick fixes and align artificial intelligence efforts with core business objectives, there is an opportunity to solidify artificial intelligence as a driver of sustained growth rather than a temporary boost.

2. Align Data and AI Governance for Compliance and Efficiency

AI governance is increasingly complex, particularly for highly regulated industries. With stringent new regulations like the European Union Artificial Intelligence Act, Forrester predicts that 40% of highly regulated enterprises will unify their data and AI governance. This shift is not only a response to compliance demands but represents a deeper commitment to transparency, accountability and ethical responsibility.

For enterprises, building a unified data and artificial intelligence governance framework can:

• Ensure alignment with global regulatory standards.

• Improve data security and transparency across artificial intelligence applications.

• Provide a structured approach to handling compliance challenges and potential risks.

By embedding strong governance, firms can protect themselves from regulatory pitfalls while enhancing overall reliability of artificial intelligence.

3. Avoid the Pitfalls of Agentic AI Through Expert Support

Agentic AI, designed to perform complex tasks autonomously, remains a challenging ambition for enterprises. Forrester predicts that 75% of firms attempting to build their own agentic AI frameworks will face setbacks due to the specialized expertise required, including complex architectures, multi-model coordination and advanced data configurations.

The recommended strategy for enterprises includes:

• Seeking support from artificial intelligence service providers and system integrators to navigate technical hurdles.

• Defining clear use cases for agentic AI to address specific business needs.

• Ensuring robust infrastructure and well-architected data solutions for scalable deployment.

Leveraging expert support helps enterprises circumvent implementation hurdles and avoid wasted resources on underdeveloped agentic AI efforts.

4. Shift IT Infrastructure to Support Scalable AI

Demand for artificial intelligence infrastructure, fueled by generative AI’s rapid adoption, challenged vendors to meet expectations. Forrester anticipates that a major vendor, such as Microsoft or Amazon could reduce its artificial intelligence infrastructure investments due to shortages and investor pressure. Enterprises should therefore anticipate increased strain on artificial intelligence infrastructure availability and prioritize resilience in their infrastructure strategies:

• Gaming server to beef up your AI infrastructure because it will give you flexibility and scalability to grow

• Monitor vendor commitments to artificial intelligence infrastructure to ensure business continuity.

• Consider alternative solutions or partnerships to mitigate potential shortages.

By building robust, adaptable infrastructures like dedicated server hosting, companies can better navigate unpredictable supply fluctuations and maintain operational stability.

5. Embrace Self-Service for Streamlined Service Desks

In 2025, Forrester forecasts that 50% of companies will transition to self-service as the primary point of contact for service desks. Advances in digital employee experiences and automated endpoint management are making self-service an efficient first contact method. Shifting to self-service can reduce response times and alleviate burdens on IT teams.

Enterprises should aim to:

• Invest in user-friendly, intuitive self-service portals.

• Automate routine troubleshooting and support tasks.

• Track and analyze self-service performance for ongoing improvements.

By optimizing service desks with self-service, organizations can foster a more efficient support experience that allows IT professionals to focus on more complex, value-added tasks.

6. Balance Artificial Intelligence and Traditional Automation

Forrester’s prediction that artificial intelligence will orchestrate less than 1% of core business processes by 2025 underscores the importance of balancing artificial intelligence innovation with traditional automation methods. While generative AI can offer rapid insights and efficiencies, current automation tools are better suited to support the scale and reliability required for core, long-running processes.

To strike the right balance, companies should:

• Recognize artificial intelligence as a supplementary tool for enhancing efficiency rather than replacing established automation.

• Integrate artificial intelligence selectively in areas where it complements, rather than complicates core automation.

• Maintain deterministic automation as the primary orchestrator of essential processes.

This balanced approach allows organizations to leverage artificial intelligence’s strengths without risking disruptions to critical operations.

7. Addressing Artificial Intelligence Development Realities

AI-driven software development is a key area for many enterprises but Forrester cautions against overestimating artificial intelligence’s impact on productivity. In 2025, at least one organization is expected to attempt replacing half its developers with AI, a move Forrester predicts will fail due to the multifaceted nature of development work.

The realistic approach is for companies to:

• View artificial intelligence as a tool to enhance developer productivity rather than a replacement for human expertise.

• Use artificial intelligence to handle routine coding tasks, freeing developers to focus on strategic, creative aspects.

• Continue upskilling teams to maximize the benefits of AI-driven tools while preserving essential human skills.

Understanding the true role of artificial intelligence in development can prevent overreliance on automation and help companies maintain productive, skilled teams.

8. Foster Innovation Through Citizen Developer Initiatives

Citizen developers — individuals outside of IT with the inspiration and expertise to use artificial intelligence effectively, are poised to become a driving force in generative AI application creation. Forrester predicts they will account for 30% of these applications in 2025. Supporting citizen developers can empower employees and increase the organization’s overall agility.

To harness this potential, organizations should:

• Provide training and resources to encourage innovation from citizen developers.

• Foster collaboration between IT and non-IT teams for streamlined development.

• Ensure AI-driven applications align with corporate security and governance standards.

Engaging citizen developers can help companies scale artificial intelligence application development while promoting cross-departmental innovation.

Conclusion

As 2024 comes to a close, companies must recalibrate their artificial intelligence strategies to focus on sustainable, long-term value. From strengthening governance and infrastructure to fostering innovation, organizations that adapt their artificial intelligence goals to meet the evolving landscape will be best positioned to achieve meaningful returns.

The road to artificial intelligence success is complex but by grounding ambitions in solid, value-oriented frameworks, companies can avoid setbacks and unlock artificial intelligence’s potential to drive future growth. Did this article help you in shifting your artificial intelligence goals the right way so your artificial intelligence initiatives will not face any setbacks? Share your feedback with us in the comments section below.