4 ways to upgrade business operations with AI
Business operations have undergone radical changes as technology has advanced. From the emergence of the internet to the rise of cloud computing, transformative shifts have upgraded old ways of working.
Organisations can seize the opportunity by optimising everyday tasks and finding efficiency gains. However, there can be barriers to progress. Challenges surrounding data, integration complexity, and culture could stall growth.
According to the ServiceNow Enterprise AI Maturity Index 2025—a survey of almost 4,500 executives worldwide to measure AI maturity—only a quarter of the organisations leading in AI maturity have implemented new workflows. The figure drops to 11% for organisations that are average in terms of AI maturity.
With these challenges in mind, here are four recommendations to transform business operations with AI.
1. Focus on people
Failure to establish employee feedback channels or foster a culture of open communication can disrupt transformation efforts. All business transformation starts with people—so successful AI implementation requires a human-centred approach.
Leaders are making changes to put people first. Our AI maturity research found that three in five organisations are working to build a culture of trust by giving teams the power to recommend AI fixes to everyday business problems.
When employees are free to voice their frustrations with workflows and suggest improvements, it creates a culture of continuous improvement for day-to-day business operations. By embedding this feedback loop into AI initiatives, you gain invaluable, real-time insight into the operational pain points that AI can help solve.
2. Reduce technical debt and data complexity
Fragmented and outdated systems are another challenge for business operations, leading to ever-growing technical debt. According to Forrester, half of technology decision-makers will see their technical debt rise to a “moderate or high level of severity” in 2025, with the number projected to hit 75% by 2026.2
To get ahead of technical debt, you must first address siloed and disparate data, which can lead to problems for AI deployment. If data is inaccessible or inaccurate, AI may be unable to produce verifiable results or the expected level of transformation.
Bringing clean, accurate data onto a single platform eliminates the risk of incorrect outputs and the need to jump between multiple disconnected systems. This transition can improve efficiency in processes such as IT support ticket routing and predictive maintenance.
3. Work towards AI-enabled outcomes
Prioritising specific, outcome-based transformations can simplify AI implementation—so you can see the benefits faster. Start by identifying where your employees’ pain points are. Process mapping can help you identify bottlenecks and prioritise the changes that will have the biggest impact on the workforce.
It’s crucial to bring together stakeholders from across departments—such as finance, HR, and legal—to ensure changes are holistic and supported. Define how you will measure the success of an AI implementation, as well as how this will be communicated to the organisation and external stakeholders.
4. Unlock new value with AI
AI agents can help improve efficiency by handling repetitive tasks for employees—empowering them to focus on more challenging, creative, or strategic work. Through automation, less time is spent preparing for strategic tasks, and more time can be spent completing them.
In HR, for example, AI agents can support the recruitment process by streamlining interview scheduling. They proactively find the best time slots for recruiters and candidates to meet, draft communications, and distribute invites to attendees.
Offloading repetitive, manual tasks to AI agents enables hiring managers to reduce time to hire. They can reinvest their time into more strategic tasks, such as designing new ways to attract talent.
AI is the next frontier for business operations, but its implementation comes with challenges. Building a strong foundation based on people, data, and outcome-led goals is the key to winning with AI.
Find out how to put AI to work for people.
1 Forrester, Predictions 2025: Technology & Security