Knowledge Hub/Prasanna Rajendran

Partner Spotlight

Prasanna Rajendran
Vice President, EMEA
Kissflow

Partner Spotlight

Beyond AI Pilots: Building the Foundation for Business Transformation

Enterprise AI is entering a more demanding phase. Early experiments demonstrated its ability to generate content, accelerate development, and support individual productivity. The next phase requires organizations to translate those capabilities into changes in how decisions are made, services are delivered, and businesses grow. For CIOs in Saudi Arabia and the wider Middle East, this puts workflow design, governance, and organizational readiness at the center of the AI agenda.

From Experimentation to Business Impact

The distance between technical possibility and operational deployment remains significant. Research published in 2025 highlighted an average of 23 generative AI proofs of concept, with only three reaching production. The challenge is carrying promising capabilities into the systems, processes, and responsibilities that shape everyday work.

At the same time, expectations are rising. A FutureScape 2026 forecast projected that 70% of Global 2000 CEOs would focus AI return on investment on growth by 2026. This broadens the CIO’s mandate. AI investments must contribute to outcomes such as faster service delivery, greater operating capacity, and the ability to introduce new offerings.

The Workflow Becomes the Unit of Transformation

Individual productivity gains matter, but their business impact depends on what happens across the full process. A document summarized in seconds may still sit in an approval queue for days. Faster code generation may deliver limited value if integration and maintenance remain unresolved.

Agentic AI creates opportunities to connect these steps. Within defined boundaries, agents can gather information, interpret requests, coordinate actions across systems, and escalate exceptions. Consider supplier onboarding: the opportunity extends from extracting document data to identifying missing information, coordinating reviews, and keeping the process moving.

Realizing that value requires organizations to reconsider handoffs, decision rights, and dependencies. The workflow becomes the unit of transformation, with success measured across the complete business outcome.

Governance as a Foundation for Scale

As agents gain the ability to act, governance becomes part of operational design. Each agent needs a defined purpose, appropriate access, a record of its actions, and clear conditions for human intervention.

For regional enterprises, decisions about data location and infrastructure must also reflect their operating requirements. These choices influence which information agents can use, where processing occurs, and how activity can be reviewed.

Establishing these foundations early gives business leaders a clearer basis for expanding deployment. It also helps IT teams manage complexity as agents begin interacting across departments and applications.

Making Value Visible

The measurement challenge is substantial: 42% of organizations worldwide report difficulty or an inability to assess returns on their digital and AI investments.

Closing that gap requires shared ownership between business and technology teams. Each initiative needs a baseline, a defined outcome, and an accountable business owner. Measures such as completion time, cost per transaction, exception rates, and service quality can reveal whether a redesigned workflow is delivering value. Ongoing operating and oversight costs must be included in that assessment.

Employees also need the skills to supervise agents, evaluate outputs, and handle exceptions. Their understanding of how work actually happens is essential to improving the process.

The CIO’s Next Mandate

The move from AI pilots to business transformation calls for sustained organizational change. CIOs must bring together technology capabilities, process ownership, employee expertise, and measurable business priorities.

The strongest foundation is a meaningful workflow that can be redesigned, evaluated, and improved under real operating conditions. Expanding from that evidence turns AI ambition into an operating capability and gives the enterprise a practical path toward lasting transformation.