CONTRIBUTOR

A small percentage of businesses are succeeding in meeting or exceeding their digital transformation targets, according to research from CI&T.

The study, carried out among 100 senior leaders overseeing digital and technology operations, unveiled just 7% of respondents had successfully met or surpassed their digital transformation objectives in the past year.

According to the survey, 93% of companies failed to achieve all their digital transformation goals, and while 58% managed to meet over 60% of their targets, 34% fell short, meeting less than 60% of their set objectives.

An intriguing correlation arose between meeting digital transformation goals and perceptions of generative AI’s impact.

Those closer to achieving or exceeding their digital transformation targets displayed confidence in the transformative potential of generative AI.

In contrast, individuals who lagged expressed skepticism regarding the technology’s benefits for their businesses.

Krishnan Venkata, chief client officer, LatentView, says in the process of any digital transformation from AI implementation to cloud adoption, there is a balance to be met between jumping head-first into the deep end and sticking one toe in at a time.

“CXOs who want to employ a successful digital transformation across an entire organization should begin by analyzing what systems are already in place and determining how integral those systems are to everyday tasks,” he says.

By identifying which processes are more heavily ingrained in legacy systems, company leaders can begin integrating innovative technologies such as AI into the mix to account for certain parts of the process.

“It is not as simple as adopting AI or GAI and abandoning the traditional method as this inevitably leads to disorganization and chaos, but rather ensuring that over time, certain processes are being replaced or accounted for with other tools and that there is still room for innovation on top of legacy systems,” Venkata adds.

The research also spotlighted several emerging use cases where generative AI is anticipated to amplify efficiency.

These areas include end-to-end software development processes, marketing strategies, customer service enhancement and innovative approaches to knowledge management.

However, the survey emphasized the importance of establishing a robust foundation for AI implementation.

Factors such as data governance, security frameworks, privacy and compliance need to be meticulously addressed to derive lasting value from technologies like large language models.

For organizations struggling to meet their digital transformation objectives, the survey recommended focusing on foundational aspects like data governance and security frameworks.

Moreover, forming strategic partnerships with seasoned organizations possessing expertise in these domains was considered crucial for both groundwork establishment and scaling AI use cases upon implementation.

Anticipating future trends, the survey indicated a positive outlook, with 66% of respondents expecting budget increases in 2024.

More than three-quarters (76%) of respondents said they either currently utilize or plan to employ generative AI within the next 18 months, highlighting a growing interest in leveraging this technology for operational enhancements.

Jasson Casey CEO of Beyond Identity, says the current AI toolset is attractive to every worker in an organization.

“Whether they’re looking to amplify their output, reduce their error rate or tackle previously untouchable problems these new tools will be irresistible to your workforce,” he says. “The key question you should be asking is how you will enable them with these new tools. Because if you are not enabling them, they will enable themselves.”

He explains by enabling a workforce with these tools, business leaders can control the framework of how data is used to train models, how bias of model training can be accounted for, and help workers decide which tools can even be employed.

“You do not want these concerns decided upon in a unique way for each project in your company,” Casey cautions.

From Venkata’s perspective, the best approaches to ensuring a balance can be struck between adoption of innovative technology and reliance on legacy systems that includes regular communication across a company.

“This ensures all processes and methods are understood and accounted for, ongoing adoption of emerging technologies on top of existing legacy platforms to gradually transition to new tools, and the flexibility to perform checks and balances and ongoing testing of new technologies to ensure that the organization continues to steer forward in innovation,” he explains.