Generative AI is Changing the Culture of Transformation and Change Management – Susmin Joseph, Turing
By Lane F. Cooper, Editorial Director of BizTechReports and Contributing Editor CIO.com
Corporate decision-makers are rapidly moving past the early hyperbole associated with generative AI (GenAI) to understand the impact that this transformative technology is likely to have on business modernization across organizational disciplines. In doing so, a new language is emerging to address the emerging relationships different stakeholders are developing across the entire enterprise technology stack to support important mission-critical business objectives through the rest of the decade.
Susmin Joseph, AVP of Enterprise Markets, Turing
These were among the conclusions of an executive dinner roundtable hosted by Turing (www.turing.com) at the 2023 CIO-100 Symposium, which featured over a dozen senior technology leaders from a cross-section of vertical industries across the United States. Representing Turing was Susmin Joseph, AVP of Enterprise Markets, who sat for an interview after the Chatham House Rule event to share the insights and observations that were discussed.
“Business leaders are realizing there’s a huge amount of transformation that can be made possible with the application of GenAI technologies,” said Joseph. “The big question is how to effectively integrate these potentially disruptive capabilities into their operations. There are clear opportunities across the board – starting with customer service and user experiences – which can deliver immediate wins.”
Fine-Tuning Speed and Flexibility
The early focus of GenAI efforts revolves around ways to enhance the productivity of different categories of employees. However, significant activity also focuses on aggregating data currently spread across complex hybrid, multi-cloud infrastructures.
“In many cases, it’s a byproduct of individuals playing with the technology. What we learned throughout the dinner conversation, however, is that senior technology decision-makers are actively looking for ways to establish frameworks and common methodologies to scale GenAI technology in support of their broader organizational mission responsibly,” he said.
To this end, specific areas are ripe for establishing enterprise-wide GenAI structures and standard operating procedures (SoPs) that accelerate go-to-market activities while enabling the flexibility needed to respond to constantly evolving markets and competitive developments.
“Today, it can take many organizations as long as 18 months to develop an idea and launch a product. Properly deployed and governed, GenAI can cut that time in half,” said Joseph.
Consequently, governance and standard practices across organizations should focus on understanding, documenting and offering guidelines for harnessing GenAI to:
Create new products and services;
Accelerate existing processes;
Redesign operations; and
Redefine how stakeholders engage with enterprise technology in general and GenAI in particular.
These categories, suggested Joseph, all work together to transform GenAI into a powerful force multiplier. And it all starts by creating new ways of talking about technology, business processes and the specific people around which all enterprise efforts revolve.
“Examples of stakeholders include developers, whose role may change dramatically by accelerating some of their development tasks, creating opportunities to build solutions that have an even bigger impact on their organizations. Business unit leaders are also important stakeholders because a solid and realistic understanding of GenAI can create new decision-making options, opening new opportunities. Even rank and file staff can enhance and augment their capabilities. And, of course, end customers would be the ultimate stakeholders as GenAI enhances vendor relationships,” explains Joseph.
Shifting to Data-centric vs. Application-centric Models
As organizations appreciate the competitive potential – and downside risks – associated with GenAI, Joseph expects organizations to focus more on the disposition of enterprise data and less on point solutions addressing the plethora of discrete problem statements that have arisen over the years – and in many cases: decades.
“One of the talking points that emerged throughout the evening discussion was that the traditional focus of IT departments – and the technology service providers that support them – has been on acquiring, maintaining and modernizing applications. How do we modernize SAP? How do we modernize Oracle and move critical application workloads from one environment to another?” recounted Joseph.
As enterprise infrastructures become more fragmented and distributed across on-prem and cloud resources, establishing effective data management, optimization, cleansing and governance discipline will become critically important.
“Effective enterprise strategies for the underlying data needed to address important problem statements is the only way generative AI can become an effective tool. With that tool, organizations have an advantage in managing rising enterprise computing complexity and creating the interconnections among their applications scattered throughout today’s heterogeneous environment,” he concluded.
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