AI is changing how software is built, how decisions are made and how businesses operate. But adopting new technology does not automatically deliver better results. The real opportunity lies in combining AI with reliable data, a clear understanding of business processes and effective governance. In this conversation with CIONOW, Jatinder Bansal, Group CIO at Arise — a pan-African developer and operator that partners with governments to design, finance, and build sustainable, high-value industrial zones and special economic zones across Africa — discusses the rise of agentic AI, the changing role of developers, the importance of business–IT partnership, and why cybersecurity must keep pace with innovation.
What trends do you see shaping enterprise technology beyond traditional automation?
AI, particularly agentic AI, will be one of the biggest changes. Earlier, we told software exactly what steps to follow. Now, AI can understand a goal, generate code, analyze information and carry out parts of a process with increasing independence.
I believe manual coding will reduce significantly, but developers will remain important. Their role will increasingly involve understanding business problems, designing solutions, validating AI-generated code, and ensuring security and reliability.
We have already seen this journey evolve from RPA to low-code and no-code platforms. AI-native development is the next step. Instead of investing heavily in tools with specific limitations and licensing costs, organizations can increasingly use AI to build software suited to their needs. The challenge is to do this securely and at scale.
The bigger opportunity is in business productivity. AI can analyze large volumes of data and identify patterns, inefficiencies and connections that people may not easily spot. This can help businesses identify cost leakages, improve quality, reduce duplication and make better decisions. The initial investment may be significant, but the potential benefits are substantial as the technology matures.
How do you see citizen development evolving as AI makes software easier to build?
Citizen development has real value, provided organizations establish clear boundaries.
Business users should be able to create dashboards, combine reports, build simple workflows and develop low-risk tools without unnecessary dependence on IT. If someone wants to bring information from different reports into a single management dashboard, there is little reason to make the process complicated.
However, the boundaries change when an application modifies transaction data, affects financial controls, changes core business rules or interacts with critical systems.
IT must remain involved in these areas to ensure appropriate access, security, integration, testing and accountability. The objective is not to restrict business users, but to help them innovate safely.
AI will make it easier for more people to build applications. That makes risk-based governance even more important. We should give business users freedom where the risks are low and bring IT into the design wherever critical data, business logic or controls are involved.
As AI adoption grows, are organizations investing enough in cybersecurity?
Cybersecurity must advance at the same pace as AI adoption. When software becomes easier and faster to develop, the number of applications, integrations and potential vulnerabilities can also increase. AI introduces additional risks because automated systems may be able to access information and take actions with limited human intervention.
In India, digital adoption is progressing rapidly, but cybersecurity maturity needs to improve further. We are having extensive conversations about AI, and we need equally serious conversations about security, privacy and responsible data use.
Consider the personal information organizations hold, including employee attendance records, phone numbers and email addresses. Companies need to know where this information resides, who can access it, how it is protected and how long it is retained. Phishing, impersonation and the misuse of personal information remain significant concerns.
India has made progress on data protection, but the real challenge is implementation. Organizations need to translate regulatory requirements into practical controls, clear accountability and day-to-day operating practices.
With AI agents, we must go a step further and define what each system is permitted to access, what actions it can perform and when human approval is required.
Cybersecurity cannot remain the responsibility of IT alone. The board, business leaders and employees all have a role to play. As AI adoption expands, security investment, governance and skills must grow alongside it.
How should organizations balance innovation with control when using enterprise data?
The approach should be based on risk rather than technology alone.
A read-only dashboard is very different from an AI application that can change financial records or critical business data. Organizations need clear rules governing what information an application can access, who can use it, what actions it can perform, whether it can write back to core systems, and how its activity is monitored.
The same principles should apply to AI agents. Their permissions should match their responsibilities, with stronger controls for sensitive data and high-impact actions.
The goal is to protect the core business while keeping the technology environment open enough to encourage innovation. Excessive restrictions can slow progress, but inadequate controls can expose the organization to risks that outweigh the benefits.
Good governance should enable responsible innovation, not become an obstacle to it.
How should CIOs work with CEOs, CFOs and other business leaders to drive transformation?
Technology transformation cannot be driven by IT alone. The people who understand the business processes must be involved from the beginning.
A common mistake is to implement something technically impressive and then expect the business to adopt it. If people do not understand the purpose, relevance or practical benefits, adoption will remain low.
The better approach is to create cross-functional teams that bring together strong business and technology professionals. For example, a supply chain transformation needs people who understand inventory, procurement and operational realities alongside those who understand the technology.
The business team knows what needs to improve; the technology team understands how it can be achieved. Both must work together to define the problem, design the solution and drive adoption.
Leadership commitment is equally important. Significant process changes can cause disruption and require adjustment during the first six to twelve months. Senior leaders must stay committed through this period and ensure the program has the necessary resources and support.
Transformation is a business change program enabled by technology, not simply a technology installation.
What skills will organizations need as AI changes the relationship between business and IT?
I see growing demand for three broad skill sets.
First, deep technology specialists in areas such as AI, data engineering, cloud and cybersecurity. Second, people who understand a business function and have enough technology knowledge to identify what is possible. Third, business experts who can work closely with technology teams to translate operational needs into practical solutions.
People who combine technology education with specializations in finance, supply chain or operations will become increasingly valuable.
The traditional separation between business and IT will continue to narrow. Business functions will increasingly develop their own technology capabilities, including AI expertise, while central IT will provide architecture, platforms, governance, security and guidance.
Business partnering will therefore become a critical capability. It helps ensure that technology investments address genuine business needs and that solutions are practical, scalable and sustainable.
You recently joined Arise. What are your immediate priorities?
My first priority is to understand the business. I have spent much of my career in manufacturing and utilities, and this is a different operating environment. I want to understand how the business works on the ground, including its operational nuances, processes and challenges.
The second priority is improving the adoption of existing technology. Organizations can invest significantly in digital solutions and still fail to realize their full value if people do not use them effectively. There are often opportunities to simplify processes, reduce duplication and automate repetitive work using systems that are already available.
Cybersecurity is another important priority. Although controls may already be in place, it is essential to review systems, servers, access rights and exceptions to identify and address vulnerabilities.
Arise also has an established digital foundation, including automated meter reading, digital mapping of industrial zones and tools that help customers understand the opportunities available across locations. The immediate opportunity is to close the gap between what these solutions can do and how effectively they are being used.
Once we have a stronger understanding of the business, better adoption and the necessary security controls, we can build on that foundation and scale AI in areas where it can deliver measurable value.
