3 AI predictions to realise business value

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The year 2024 was one of rapid AI experimentation. For leaders across Europe, the Middle East, and Africa (EMEA), 2025 will be the year of value realisation—with more companies determining how they’ll innovate to drive success.

More than one-third (38%) of executives globally worked to link AI objectives to enterprise goals in 2024, according to the ServiceNow Enterprise AI Maturity Index. Yet only 18% felt they’d applied the technology to its full transformational potential.

The research results reflect my own experience in speaking with customers and partners. Some use generative AI (GenAI) to brainstorm new ways to think about a problem. Others have built AI-powered workflow automations to handle repetitive tasks. The common thread is that AI helps people work smarter.

Every leader I speak to differs in their approach to AI for their business and pace of adoption, depending on their industry, department, and country. Based on my conversations with leaders in EMEA, here are three AI predictions that I believe will define how businesses realise the value from the technology.

1. Businesses seek high-quality data

Nearly two-thirds (65%) of organisations regularly use GenAI, according to McKinsey. Whilst some trailblazers of the AI revolution have succeeded, other projects have failed due to unclean or inaccurate data.

Robust data underpins the success of AI implementations—it’s needed to train AI models, assess their effectiveness, and inform decision-making.

At the proof-of-concept stage, development should be based on real data and comprehensive model training. However, the true value—and where we need to be operating more—is in the proof-of-value stage, where business problems are identified and data is used to solve them.

To get the most value from AI projects, organisations must bring together:

2. AI governance becomes a C-suite priority

Digital transformation has ramped up in recent years, and tech stacks have proliferated. Procurement of new tools and systems has taken control of IT budgets—and it hasn’t all been above board.

Shadow IT, or the unregulated growth of apps and devices outside of IT’s knowledge, has created data silos, compliance risks, and inefficient workflows. As AI extends further into mainstream business, governance will be top of mind—leaders are keen not to repeat the digital transformation mistakes of the past.

Errors in governance, such as failing to address algorithm biases during training, can erode trust with employees, customers, and partners. Equally, breaches of data integrity and security can pose large reputational, trust, and financial challenges.

Focusing on governance involves more than managing these risks. Legislation such as the EU AI Act will make good governance a business imperative in the face of regulatory penalties for noncompliance. This is sure to force the topic onto the C-suite agenda—with execs leading the charge in embedding AI governance into the organisation’s culture.

3. Leaders prepare for greater AI collaboration

One of the biggest developments in the AI landscape won’t be technological. It will be cultural. As AI adoption increases, new workforce skills will be needed—leading to an emphasis on developing employees’ AI skills.

Not everyone will need to know how to code or engineer a large language model (LLM). Instead, learners will grow and enhance their skills to become AI-capable and implement the technology effectively within their roles. This will equip staff to work seamlessly with intelligent assistants such as Microsoft Copilot and ChatGPT to augment their work.

The augmentation of roles, as opposed to their replacement, is the future of work. Leaders will recognise the shift and support workers with AI systems and resources to realise the value of AI. Every role will evolve with AI as an assistant, creating a powerful combination that will shape the future of work.

Find out how ServiceNow can help your organisation put AI to work for people.