AI and generative AI are now necessary tools for business success and growth.
Key takeaways
CIOs and CTOs are tasked with creating AI strategies and integrating tools and applications.
IT leaders can implement proven AI plans to increase insight, reduce risk and achieve success.
The middle market is experiencing a surge in the integration of artificial intelligence and AI technologies, as companies seek new avenues for enhanced productivity, efficiency and creativity. With AI and generative AI now necessary tools for business success and growth, chief information officers and chief technology officers have the responsibility of developing and implementing an effective AI strategy and determining how and where to integrate AI tools and applications.
Demonstrating the reach of AI in the middle market, the RSM Middle Market AI Survey 2024: U.S. and Canada found that 78% of executives surveyed are either formally or informally using AI. But only 20% of those respondents feel they have integrated AI meaningfully, and 67% using generative AI reported they need outside help to get the most out of that tool. With the growth and potential of AI solutions, CIOs and CTOs have a significant opportunity to transform key processes and shape the future of the business.
Diego Rosenfeld, a principal at RSM US LLP, along with RSM US directors Robbie Beyer and Jason Proto and David Brassor, a managing director at RSM Canada, recently examined the role of technology leaders in AI strategy and deployment during RSM’s webcast Cracking the AI code: A CIO’s guide to practical implementation.
Below, we take a look at some critical details for CIOs and CTOs to consider when developing an AI strategy, as well as potential use cases and examples of successful AI implementation.
The role of the CIO and CTO in AI adoption
Many information technology organizations are being asked to become more innovative and integrate with the business, bringing technology solutions to the forefront that can help drive transformation. CIOs and CTOs obviously have a large responsibility in this overall transformation, with AI deployment joining an ever-growing portfolio of capabilities for the role.
However, rolling out the technology is not a simple endeavor. Brassor outlined a potential scenario in companies that may not fully understand the challenges related to AI implementation. “With many organizations, it’s very easy to slap a credit card down and procure cloud services and procure additional AI services,” he said. “But you’re invariably putting the organization at risk by doing that.”
With many organizations, it’s very easy to slap a credit card down and procure cloud services and procure additional AI services. But you’re invariably putting the organization at risk by doing that.
David Brassor, managing director, RSM Canada
Instead, technology leaders need to establish the importance of effective management of the AI portfolio and responsible AI governance. Many businesses are in the early stages of requesting AI, and their often overly cautious approach to adoption may leave users feeling unable to drive the expected benefits.
Establishing the right level of business enablement within the overall CIO and CTO organizational structure is crucial. AI can be embedded within a number of core business applications, including enterprise resource planning, customer relationship management (CRM) and IT service management.
CIOs and CTOs have the critical responsibility of determining the strategic vision for the organization’s AI adoption, including how to embed AI into the overall infrastructure and integrate it with existing technology.
Employee upskilling and support are also key elements of successful AI adoption. Currently many users are very early adopters of AI. Technology executives need a strategy to upskill end users so they're comfortable with using AI and understand its benefits, as well as IT and security teams to ensure they are effectively and safely implementing AI solutions.
With the massive potential of AI solutions, many companies are performing business value calculations to understand the return on investment of their early deployments of AI and robotic process automation. However, the returns may not show the expected value, often because investments may not have been properly directed initially. CIOs and CTOs need to ensure that AI use cases drive value for the organization.
Key issues
As with other key business initiatives, an effective AI strategy starts with good data governance, which requires close oversight of data, starting from onboarding and continuing through its full lifecycle within the organization.
“If you have the governance, good data and the controls around it, you will be more successful with your AI implementation,” said Proto. “If you don’t have those things in place, we are finding there’s a high failure rate with those AI projects, or the decision making that’s coming out of those AI models is often flawed because of data inaccuracies.”
If you have the governance, good data and the controls around it, you will be more successful with your AI implementation. If you don’t have those things in place, we are finding there’s a high failure rate with those AI projects, or the decision making that’s coming out of those AI models is often flawed because of data inaccuracies.
Jason Proto, principal, RSM US
Without strong data governance, AI solutions can create hallucinations or simply generate inaccurate model output. Technology executives need to consider how to mitigate risks and implement effective data governance before selecting AI tools and strategies and planning implementations.
For example, effective data governance could include using a master data management or another data management system to oversee the data throughout its lifecycle. In addition, a company could leverage data quality and data duplication rules that govern data from onboarding to deprecation.
Challenges and opportunities
When designing and implementing an AI strategy, CIOs and CTOs should keep the following key priorities in mind:
Data privacy and security: Technology executives ultimately responsible for making sure that data collected and used by AI systems is secure, complies with privacy laws and doesn’t leak outside the organization.
User experience: Adoption and outcomes are heavily dependent on solutions providing an exceptional user experience.
Setting expectations: Technology executives must develop processes to help team members understand the technology and how they can use it, driving innovation across the enterprise.
Interoperability and integration: Integration with existing infrastructure and technology is critical to maximize the utility of AI solutions.
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Scalability and flexibility: To support their adoption and continued success, solutions must meet the growing needs of the organization, creating a flexible framework that can adapt to changing circumstances.
AI use case successes
While AI development and implementation can create additional challenges and potential risks, RSM has worked with many CIOs and CTOs to develop strategies to drive AI success within their organizations. AI use case successes include:
- AI governance: By establishing a comprehensive AI governance strategy, a client gained clarity on their current disparate data sources and business workflows, uncovering critical challenges and opportunities within the organization. With the strategy in place, they could define their current-state maturity and build a roadmap to guide their investments, align with business objectives and become an innovator in their industry.
- CRM AI enhancement: A client implemented a CRM platform that housed all their customer information, but integrating generative AI elevated its potential. Now, users can utilize a pop-up within the CRM pane that automatically pulls in the customer information and generates personalized messaging and content to send to the customer. The tailored messaging has much higher open and response rates than general email blasts.
- AI data analyst: In the past, analysts or business users who may not be very technical have been tasked with connecting to a data source that is established as a source of truth and building their own dashboards. Now, AI is bringing new capabilities over structured data. In a chat experience, AI can generate dashboards from scratch, create helpful visuals and KPI cards from scratch or even ask follow-up questions to drill down further into data and uncover new insights. It creates a powerful tool to get answers to questions and make decisions rapidly.
Frequently asked questions
AI can transform your customer interactions, from delivering more extensive self-service solutions that increase accessibility to integrating AI-powered chatbots that replicate human conversations that provide key information and solve problems.
AI can strengthen your infrastructure by automating tasks, delivering more efficient data analysis and providing insights for more effective decision making.
Effective AI governance is critical to enhance cybersecurity and data privacy efforts, creating a framework for how sensitive data and intellectual property is shared.
Technology executives can take advantage of several AI capabilities that align with business goals, including creating efficient and accurate data analysis, predicting customer behavior, enabling effective demand planning and rapidly detecting anomalies that could signal potential challenges.
You can leverage AI to automate marketing campaigns, with more creative and consistent communications and personalized experiences that can encourage more customer engagement.
While AI tools and applications will have upfront costs, an effective AI strategy can help you do more with less and optimize costs moving forward by streamlining operations, boosting productivity, strengthening resource management and establishing predictive maintenance capabilities.
The takeaway
Developing an effective enterprise AI implementation strategy can seem overwhelming, and many organizations may not know where to start. But while every company may have different goals for AI, technology leaders can follow common, proven strategies to increase insight, reduce risk and achieve greater success.
“The big thing is to not be afraid to jump in and start your AI journey,” said Beyer. “We've seen a lot of organizations that have been hesitant around AI. Obviously understanding all the risks is incredibly important. But the benefits to your organization can be incredible, and we've seen so many companies driving significant performance improvements by leveraging AI.”
The big thing is to not be afraid to jump in and start your AI journey. We've seen a lot of organizations that have been hesitant around AI. Obviously understanding all the risks is incredibly important. But the benefits to your organization can be incredible, and we've seen so many companies driving significant performance improvements by leveraging AI.
Robbie Beyer, director, RSM US
Ready to get started? RSM’s experienced AI advisory team understands the enterprise AI journey and the foundational elements necessary to generate increased value and reduce risk. Contact our team to learn more about how AI can transform your key business operations.
RSM contributors
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David BrassorManaging Director
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Jason ProtoPrincipal
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