Business must prepare for the AI grind

AI made a side entry into the enterprise this year and spread rapidly, exceeding 2024 AI prediction that 60% of workers will bring their own AI (BYOAI) in 2024. 

This was a key finding in Forrester’s Q2 AI Pulse Survey, 2024, which shows many concerns about generative AI (genAI) use at US organisations, such as hallucinations, finding quality training, and challenges around governance and data protection.

“But BYOAI is not a strategy,” says Forrester. “Enterprise AI leaders now realise that for longer-term AI success, they need an effective strategy combining data and AI to ensure AI enters through the front door. This accentuates the need for a strategy that evolves with the rapid pace of innovation. 

“The strategy must include estimating business impact and ROI, selecting the right use cases, plans for cleaning and governing data, aligning on an operating model, training talent, experimenting with new application architectures, partnering internally and externally, and balancing risk and reward. “

“This will not happen overnight. In the year ahead, you’ll need to put your nose to the grindstone to develop an effective AI strategy and implementation plan. In 2025, organisational success will depend on strong leadership, strategic refinement, and recalibration of enterprise data and AI initiatives commensurate with AI aspirations.”

Forrester has made the following predictions for 2025:

• Most enterprises fixated on AI ROI will scale back prematurely. 

Enterprises are achieving improved customer experience, employee productivity, and even new revenue streams with AI use. But an AI reset is underway. Obvious use cases that enterprises experimented with last year are now table stakes and embedded in business software. Leaders are realising that ROI from investments will take longer than they anticipated, and are shifting toward pragmatically delivering ROI over time. In Forrester’s Q2 AI Pulse Survey, 2024, 49% of US genAI decision-makers said their organisation expects ROI on AI investments within one to three years and 44% said within three to five years. 

• Thirty percent more large-firm CIOs will bring CDOs into the IT fold. 

CIOs will be tapped by CEOs to lead AI technology efforts and will realise the need to bridge the gap between technical and business expertise. Enter the chief data officer (CDO). CDOs and other senior data and analytics leaders are chameleons, equally comfortable in an IT organisation or in a line of business. Forrester’s State Of Data, Analytics, Measurement, And Insights Survey, 2024, shows that 39% of respondents note the most senior data and analytics leader reports to the CIO, while a similar share (37%) say they report to the CEO. 

• 40% of highly regulated enterprises will combine data and AI

governance. 

The enforcement of the EU AI Act in February 2025, with fines of up to 7% of firms’ global turnover, and a potential AI tax and fines in the US will require integrated governance. Since AI is a data app and AI governance is data governance, 40% of highly regulated companies will combine their data and AI governance programs. Compliance capabilities depend on visibility into how AI models use data and the nature of the data itself. With no universal templates, standards, or certifications, companies must urgently engage with third parties to create a new shared responsibility model and avoid repeating past data governance failures, as AI governance is highly complicated by its rapid pace and complexity.

• The AI pendulum will swing back to predictive AI for over 50% of use cases.

According to Forrester’s Q2 AI Pulse Survey, 2024, the distribution of enterprise use cases leveraging predictive AI (36%) is roughly equal to those leveraging genAI (35%). However, as enterprises hit transient roadblocks in applying genAI in ways that meet expectations, organisations will double down on predictive AI applications. Tried-and-true predictive use cases like predictive maintenance, customer personalization, supply chain optimisation, and demand forecasting will siphon investment dollars away from genAI-specific use cases in 2025.

• Three out of four firms that build aspirational agentic architectures on their own will fail. 

AI agentic architectures were a top emerging technology for 2024, but they’re not ready yet — expect another two years before they have any chance of meeting inflated automation hopes. Meanwhile, agentic AI is all the rage as companies push genAI beyond basic tasks into more complex actions. The challenge is that these architectures are convoluted, requiring multiple models, advanced RAG stacks, advanced data architectures, and specialised expertise. Aligning these models for focused outcomes is an unresolved issue that will disappoint eager developers. As a result, 75% of enterprises that attempt to build these agents themselves next year will fail and will turn to consultancies to build custom agent setups or will use agents embedded in their existing vendor software ecosystems.