What CIOs need to know about using AI agents for business transformation

As a CIO, you’re no stranger to the excitement surrounding AI and its potential to transform your business. The rapid evolution to gen AI and agentic AI means it is time to take a closer look at the incredible opportunity to drive real business value with this technology. 

AI has the potential to transform every aspect of a business, from customer experience to operations. At IBM, we really do believe the future of work is not about humans versus machines; it’s about humans and machines working together to achieve better outcomes. I’ll borrow from another leader who said, “AI is like Tony Stark with the Iron Man suit on.” 

My team would tell you I’m a cynical optimist, but make no mistake, I am a huge optimist when it comes to using AI agents and AI assistants to drive business transformation. My optimist fundamentally believes in enterprise productivity with AI. Moreover, I believe that we can only reach our potential with an open approach. I see these tools as essential for automating routine tasks, providing real-time insights, increasing team effectiveness, and enhancing customer experiences. 

Yes, there is a very real divide between this optimistic potential and the technical demands of realizing said potential. As a CIO, it’s a divide I navigate every day. The problem is that in a rush to use the shiny new toy (read: AI), many CIOs and tech leaders just add chatbots or copilots on top of existing software without having a clear strategy and ability to integrate AI at a deeper platform level. 

To harness the value of AI for enterprise productivity, the business needs to take an introspective moment about how it operates, and the mindset that drives those operations.  

What it means to become an AI-first enterprise 

Let’s level-set first: AI is not just about automating tasks, it’s about augmenting human capabilities to help us make better decisions, work more efficiently, and focus on higher-value projects. 

AI-driven transformation requires a cultural shift within an organization. From leadership to the newest employee, a business culture must be one that is willing to experiment, learn from failures, and adapt quickly to new ways of working.  

Becoming a gen AI-first enterprise means putting AI at the forefront of your business strategy and leveraging its capabilities to drive transformation across the organization. It does not mean using AI all the time, every time, just for the sake of saying you did. It is strategic and purposeful and, yes, entirely doable. 

Getting started with AI agents for productivity 

As a CIO, you are uniquely positioned to harness the incredible potential of AI agents to transform your business. The journey to fully capitalize on AI begins with integrating it seamlessly into your existing infrastructure. Here are a few key steps to get started: 

1. Integrate AI with existing systems 

2. Ensure data is high quality and trustworthy 

3. Unite the team around an AI-first culture 

Integrating AI with existing systems  

In basic terms, an AI agent is a tool. One with great power and potential, to be sure, but still it needs to be used correctly in order to reach its potential. 

Think about your legacy systems as a vintage race car. Even though it was created in an era of older technology, the potential is there. You just need some select modernizations to ensure the latest and greatest technology can integrate with it. Do that and you’re racing stronger again than before. 

We’ve seen firsthand what it looks like to try using AI agents before addressing critical platform integrations and data format inconsistencies. Outdated and siloed systems can be blockers to AI adoption. So, what can you do?  

1. Map out critical workflows 

2. Identify bottlenecks 

3. Prioritize integrations to eliminate targeted data silos 

For my team, we included optimizing infrastructure and application environments, as well as redesigning our end-to-end business processes. We invested in API-first architectures, strategic platform partner solutions, and IBM’s automation tools to help streamline interoperability between legacy and modern systems. 

Use an enterprise’s own high-quality data  

Alongside interoperability solutions, as client zero, we prioritized using high-quality data that drives explainability, transparency, and trustworthiness. IBM shines in this area, so I have faith in the data we use to train our models and prompt our own AI agents.  

Getting your data ready for AI requires an AI-first mindset that includes accountability, transparency, and explainability, all established through clear governance policies and guidelines. This means: 

1. Integrating data from multiple sources and systems 

2. Addressing unorganized or siloed data 

3. Methodically and responsibly curating and preparing data 

4. Establishing governing practices for the responsible and ethical use of AI 

The way I see it, responsible AI practices are a required part of the AI strategy. Companies that have those practices woven into their solutions, as IBM does, will be positioned to respond to challenges AI solutions might present in the future. 

Uniting around an AI-first culture 

Ever heard the Peter Drucker quote, “culture eats strategy for breakfast”? Well, I agree with him. And implementing AI agents into our business practices is a prime lesson in how powerful culture can be, for better or worse. Humans often resist change because they think it will bring a negative impact. Resistance to AI is no different, and it can hinder adoption and value realization. 

Remember my earlier points around becoming an AI-first enterprise? That is a culture transformation as much as a digital transformation. And I, ever the optimist, believe that cultures can change for the better; I am seeing it firsthand at IBM. 

How can you help foster an AI-first culture in a positive way?  

• Leadership buy-in and role modeling. At IBM, we work to foster an AI-first culture with top-down support and continuous learning for all. It’s not lip service. The buy-in must be visible for this kind of cultural transformation to take hold. So maybe you start small and get some wins. When my team implemented AI-driven automation and reduced manual tasks it resulted in cost savings and efficiency gains that helped earn organizational buy-in.  

• Cross-functional collaboration with a common mission. CIOs are in a great position to break down silos and create spaces for diverse teams. We sit with the rest of the business leaders, and we talk with the techies working for us. We know how to connect data scientists, domain experts, and business leaders on AI projects. We unite people with a shared mission to use AI agents for the betterment of employees, clients, and the business. This shared understanding and ownership of AI solutions is what helps shift the culture. 

• Celebrate human-technology synergies. I am a staunch advocate for retaining the human touch in work processes. So much so I even have a podcast about it! I said it before and it is worth repeating: AI agents should augment humans, not replace them.  

Encourage a growth mindset. Cultivate an environment where your employees feel they can and should continue to learn about evolving tech like AI. Enable upskilling and reskilling that allows your employees to feel they are in better control of the AI tools they can use. And then allow them to experiment, learn more and iterate processes for growth. 

I’m proud that IBM champions this mindset and the experimentation that comes with it. Through it all, human oversight and emotional engagement remain core to our interactions with each other and with clients. 

The future is now: Business transformation with AI assistants and agents 

AI offers transformative opportunities for businesses, from automating multi-step tasks to providing real-time data-backed recommendations. Three ways my team uses AI right now: 

• Interacting with the users of our IT Systems (e.g., AskSales and AskProcurement) 

• Partnering with clients to unlock contract intelligence (e.g., the Sirion Labs collaboration)  

• Helping conduct robust testing of our complex and interconnected enterprise systems and environments 

As a CIO, I see it as my role is to ensure our AI solutions are effective by identifying, mapping, cleaning, and leveling out any bumps in the process. With this deep understanding of AI technologies and a proactive AI-first approach to any roadblocks, I’m confident we can unlock enormous productivity gains and drive greater business transformation with AI agents. 

To learn more about how IBM can help you orchestrate AI across your business, visit IBM watsonx Orchestrate.