What’s Ahead in AI for 2025?

As we enter 2025, artificial intelligence (AI) will continue to be a major theme. From foundational readiness to advanced applications, organizations are both excited by and challenged with integrating AI into their operations. Based on our research at TDWI, here are four trends that I see shaping the AI landscape in 2025.

1. Preparing for AI Adoption: Building the Foundation

In 2025, one of the most pressing priorities for organizations continues to be preparing for AI adoption. This includes addressing gaps in organizational readiness, data quality, operational capabilities, and governance.

In the TDWI AI Readiness Assessment, taken by hundreds of organizations, the median score is 59/100, indicating that most companies are still at the “standardizing” stage of readiness. While data foundation readiness is progressing, gaps persist in areas such as skills readiness and operational readiness—critical for deploying AI models into production.

With many companies feeling under pressure to “do something” with AI, doing it right requires a solid foundation. In 2025, expect organizations to:

• Continue to strengthen their data infrastructure to ensure high-quality, trustworthy data
• Begin to develop AI strategies aligned with business goals
• Begin to invest in governance frameworks to address the ethical and responsible use of AI

2. The Evolving Role of AI in BI

AI is reshaping business intelligence (BI) tools, particularly with the advent of generative AI. Natural language processing (NLP) interfaces and automated insights are making it easier for users to interact with data. These innovations democratize access to data, empowering business users to derive value from both structured and unstructured sources.

One major trend I see for 2025 is the increasing use of generative AI as a front-end interface for querying company data. Many organizations are exploring whether they still need traditional BI tools, given the capabilities of generative AI. However, it’s not as simple as replacing BI platforms. Tools need to ensure that AI-generated insights are accurate and responsibly governed. BI vendors are countering the perceived threat by incorporating user-friendly features and guardrails into their platforms.

This interplay between AI and BI will be a focal point in 2025, as organizations navigate how best to leverage these tools for decision-making.

3. AI Guardrails Take Center Stage

With the rise of generative AI, the need for robust governance frameworks is critically important. In TDWI surveys, over 60% of respondents reported that generative AI has increased their urgency to address responsible AI practices. That is good news.

In 2025, guardrails for AI will be critical in multiple areas including:

• Data governance: Organizations will need policies for managing diverse data types, including unstructured data, as it becomes more integral to AI applications.
• Model governance: Ensuring that AI models are ethical, unbiased, and explainable is essential as more models move into production. The models themselves will need to be better governed, in addition to the data feeding the models. We’ve been talking about this for years at TDWI. In 2025, this will become more important to organizations.
• Ethical AI: AI legislation is advancing globally, with themes including privacy, workforce impact, and fostering innovation driving new regulations. The EU AI Act, along with U.S. state and federal laws, will compel organizations to adopt ethical frameworks and practices.

As organizations deploy more AI, these guardrails will move from theoretical discussions to practical implementations, ensuring that AI is used responsibly.

4. The Emergence of Agentic AI

One of the most exciting trends for 2025 is the rise of “agentic AI.” Derived from the concept of “agency,” this new form of AI refers to systems that can act autonomously toward specific goals, often without continuous human oversight.

Imagine a travel-planning AI application that autonomously integrates services to build an itinerary, find tickets, and make purchases based on your preferences. This evolution of AI bots into autonomous agents can open the door to new applications.

Marketplaces offering pre-built AI models and services are also expanding. AIxplain, for instance, already boasts a marketplace with 35,000 AI models ready to be integrated into workflows. However, building and deploying agentic AI applications requires specialized skills, which many organizations are still developing.

In 2025, expect significant growth in the creation and use of AI apps, especially as organizations begin to leverage these agentic capabilities to streamline operations and deliver innovative customer experiences.

Conclusion

For organizations embarking on their AI journey in 2025, success will depend on thoughtful, business-driven strategies. Here are some key steps to consider:

• Define AI use cases: Start with clear, business-aligned objectives. AI should solve real problems and create measurable value.
• Build the data foundation: Ensure data is high-quality, trusted, and well-governed. This includes thinking beyond structured data to unstructured and streaming sources.
• Foster AI literacy: Create a culture that understands AI’s potential, limitations, and ethical implications. Encourage critical thinking skills among those interacting with AI-generated outputs.
• Adopt a data-driven approach: Recognize that data is the backbone of successful AI applications. Consider how your data will be used in AI models and ensure it supports your desired outcomes.

As we move forward, the emphasis will remain on balancing innovation with responsibility. AI’s potential can be considerable, but its success depends on thoughtful implementation, governance, and alignment with business objectives. Let 2025 be the year your organization takes meaningful strides toward realizing the promise of AI.