Riya handles business-to-business (B2B) machine learning applications across the EU and North America. She used to work as a writer covering AI and data analytics for the Times of India Group. She lives in Toronto.
There are now dozens of GPT-driven products available, and hundreds more are being developed. Together, these tools seek to turn conventional roles and procedures into dynamic, parallelized workflows through the use of AutoGPT and other LLM model variations. Developer productivity is increasing significantly thanks to tools like GitHub Copilot, which is driven by OpenAI’s Codex. Some studies have found that work completion speeds can increase by up to 55%.
Strong change management and thorough consideration of intellectual property protection are crucial given the rapid deployment of genAI in order to guarantee successful integration and preserve sensitive data.
In an interview with Craig Mackereth, EVP-Global Service Delivery, Rimini Street, on the “AI in Business” podcast, Senior Editor Matthew DeMello talked about how financial services IT teams are excited to test generative AI (GenAI) and stressed the value of experiential learning, change management, and cautious adoption because technology is constantly changing.
In the analysis of their conversation that follows, we look at two important findings.
Strong change management and IP protection: creating and putting into practice effective change management plans to assist IT departments and safeguard intellectual property, guaranteeing a smooth AI integration while preserving control over private information.
Prioritizing AI projects that offer a definite return on investment (ROI) within the first year is known as “centering AI initiatives around ROI.” A systematic approach to AI implementation is fostered and financial sustainability is ensured from the start by a commitment to quantifiable ROI, which also generates confidence and support.
Strong Change Management and IP Defense
Craig begins the episode by outlining the three main obstacles financial services organizations must overcome in order to embrace and incorporate generative AI:
Future Success Uncertainty: Although gen AI has generated a lot of buzz and investment, it’s uncertain which players or strategies will ultimately succeed. Choosing the wrong strategy could be expensive, and this uncertainty makes it hard to know where to invest.
Leakage of Intellectual Property (IP): Gen AI entails feeding models content, frequently proprietary IP. Concerns exist regarding the usage, management, and protection of IP at every stage. Businesses must know if they are maintaining control over their intellectual property or if they are ceding some of it in favor of more expansive capabilities.
Change Management: Effective change management is necessary for AI initiatives to be implemented successfully. Understanding how AI will be implemented and how it will affect the company is more important than simply asserting that it can solve problems. In order to keep valuable team members from feeling excluded or thinking about leaving if they believe their abilities are becoming obsolete or undervalued, it is imperative that IT teams be included in this journey.
He continues by stressing the significance of making strategic decisions while implementing AI in the context of digital transformation. He asserts that leaders must distinguish between truly transformational AI projects and simple tinkering. They need to think about whether AI is consistent with their brand’s values or if its unpredictability presents concerns.
“If you’re choosing between situations where AI makes sense and ones where it might harm the brand.” Here is the kind of company choice that needs to be made by the leaders. It is surrounded by the question, “Am I truly undergoing a digital transformation or am I merely gaining experience?”
— Craig Mackereth, Rimini Street’s Executive Vice President of Global Service Delivery
Craig emphasizes the necessity for prudence in the conservative financial services sector, where trust is essential, as his team has been utilizing AI since 2019. He counsels executives to make sure AI improves rather than damages the reputation of their company.
He goes on to stress that a cautious or defensive approach to gen AI won’t be feasible for a very long time. He believes that corporate, controlled usage of this technology is beneficial, particularly when sensitive data and a brand’s reputation are on the line. He does, however, note that it is difficult to take a conservative stand because of how flexible and ever-changing the modern technological libraries are.
Craig emphasizes the value of exercising caution and responsibility when handling sensitive material by drawing on his background in the finance, defense, and aerospace industries. In many industries, rapidly evolving and unproven technologies are generally not trusted or utilized for crucial company processes.
Putting ROI At The Center Of AI Initiatives
He stresses the significance of new technology adoption at the business level. He points out that every new generation of technology must be applied and used in the actual world. Craig points out that non-competitive cooperation can be advantageous without endangering competitiveness in fields including cybersecurity, charity endeavors, and consumer education on credit.
Craig stresses that just because the initial generation of AI is new, it shouldn’t be written off. He recommends seeing it as a fundamental building piece for resolving practical business issues that yield ROI. Since successful initial initiatives open the door for additional research and investment, he counsels financial service CEOs to begin with AI projects that exhibit obvious value.
“You need to take a closer look at a project if it is unable to pay for itself in the first year and the team working on it is unwilling to support the promise that it would recover all of its expenses in that first year. In the event that they guarantee a return on investment (ROI) and that the ROI will occur within the first 12 months, then you should invest because it’s a building block in such case. Continue to catch up with first- or second-generation. You’re on the field, playing the game, and performing some AI work.
-Craig Mackereth, Rimini Street’s Executive Vice President of Global Service Delivery
He concludes by highlighting the importance of including the IT staff in AI initiatives, pointing out that they would inevitably want to try out and interact with the technology. He emphasizes the value of change management and cautions executives against undervaluing the IT team’s eagerness for practical experience and experimentation.
As Craig states, “The best way to learn something is to break it, and then fix it.” This emphasizes that failure in early initiatives shouldn’t be seen negatively. He claims that because AI is unpredictable, not all results can be predicted and that early failures can pave the way for big future achievements. Instead of completely discounting these situations, it’s important to use them as teaching moments.