ServiceNow World Forum 2026: Three Key Takeaways on AI

Last week, ServiceNow hosted the World Forum 2026, where we had the opportunity to see how technology, and particularly AI, is impacting businesses and transforming the way services are delivered.

A few years ago, many discussions centred on what AI could do and potential use cases – including replacing human labour. Today, the conversation seems to be changing towards how firms can use AI effectively, responsibly, and at scale.

The event focused on real-world implementations aimed at improving information management, asset visibility, and governance through more integrated workflows and operational data models. Hear are our key takeaways.

1. AI is about people

The AI narrative is often centred on creating value for customers and end users, but there is another stakeholder that is frequently overlooked: employees.

The discussion around AI replacing humans is gradually shifting, as businesses are realising that the real value lies in how people use AI to support the organisation, rather than simply automate tasks.

According to ServiceNow research, there is a strong appetite among employees to embrace AI. The figures show that 71% of employees believe AI improves morale and job satisfaction, compared with only 45% of executives. Additionally, 67% say AI allows them to focus on higher-value work.

However, organisations are not keeping pace with this enthusiasm. The skills gap remains significant, with 42% of employees reporting that they are not receiving enough AI training, while only 21% of organisations have assessed AI skills across their business.

Leaders should consider this a strategic priority. In highly competitive environments, AI training is not only necessary but also an important tool for talent retention. Organisations that provide tailored, ongoing training are 2.6x more likely to achieve stronger employee engagement and retention.

In practice, AI should take on repetitive and routine tasks, allowing people to focus on judgement, relationships, exception management, and effective decision-making.

2. Don't burn dollars. Get the fundamentals right

Investment is no longer the primary constraint. AI spending increased by 110% in a single year, and AI is expected to account for 20.4% of IT budgets by 2027, up from 13.1% today.

However, returns depend more on strong foundations than on spending levels.

Only 16% of organisations have replaced fragmented legacy systems with an integrated platform. At the same time, the proportion of organisations with AI-enabled workflows integrated across functions has fallen from 30% to 16% as "agent sprawl" has increased. AI-enabled workflows remain the lowest-scoring maturity pillar, achieving only 40 out of 100.

The data clearly shows that ROI increases alongside AI maturity:

• 125% ROI for Experimenters
• 145% ROI for Scalers
• 159% ROI for Advancers
• 210% ROI for Transformers
  

Leaders report an average ROI of 160% today and expect this to rise to 194% within the next two years, alongside a 5.6x increase in productivity and a 2.7x greater ability to scale.

The lesson is clear: before making significant investments in AI, organisations should focus on simplifying processes, integrating data, and establishing strong operational foundations. That said, this should not prevent firms from experimenting with AI in a controlled manner. Piloting targeted use cases can help build capabilities, demonstrate value, and identify lessons learned while the underlying foundations continue to mature.

3. Adoption must be controlled and secure

AI maturity is a journey, not a leap.

According to ServiceNow, the Global AI Adoption Index increased from 35 to 51 out of 100 in 2026. Most organisations remain in the Scaler (57%) or Experimenter (21%) categories, while only 4% have reached Transformer status.

At the same time, Agentic AI is spreading faster than organisations can govern it. While 59% of organisations are already using Agentic AI, only 9% have implemented fully autonomous, multi-step workflows.

The adoption of AI in the workplace is inevitable, but failing to establish an appropriate governance framework introduces significant risk.

Research shows that 69% of organisations have employees using unsanctioned AI tools, commonly referred to as "Shadow AI". On average, these tools take 400 days to be discovered. Even more concerning, only 13% of organisations report having a defensible security posture.

This is why getting the basics right remains so important. Maintaining an effective CMDB and adopting frameworks such as CSDM provides organisations with greater visibility of their IT assets, enabling the establishment of a reliable, accountable, and governed lifecycle for technology and AI services.

Final Thoughts

It is understandable to feel concerned about new technologies and rapid developments. However, the best strategy for embracing change is education.

Closing the skills gap and putting people at the centre of the transformation journey is essential.

We live in a world that operates at machine speed, and humans alone cannot keep pace with that level of change. Skilled professionals, supported by technological enablers, should remain at the core of organisational strategy. The objective is not simply automation, but the reduction of operational burdens, enabling people to focus on decision-making, critical thinking, and value creation.

Success will ultimately depend on integrated data, strong governance, and reliable information that provides better business and risk intelligence, not on the number of autonomous agents
For now, the good news is that -we- humans are still in control.

Where to start: stop AI chaos, start controlling

At Pulsar, we integrate AI Control Tower with your broader operating model – connecting to IRM for unified risk management, SPM to align AI investment with strategic priorities, and SecOps to protect your AI.

We’ve developed a 12-week AI Control Tower Launchpad to help organisations get this right from the start. We stand up the platform, integrate it with your risk and security processes, onboard your first wave of AI use cases, and train your team to run it independently.