Top 5 Challenges CIOs Will Need to Overcome to Make Generative AI Work for Them

  • Posted by: Recode

Following the November 2022 release of ChatGPT, there has been a surge in business interest in generative AI. In its August 2023 report, Enterprise Strategy Group (ESG) noted that 54% of organizations plan to adopt generative AI over the next 12 months. Likewise, a recent Gartner report outlined that 45% of business executives plan to increase their investment into generative AI.

Many large organizations are already embarking upon generative AI-powered initiatives. For instance, in August this year, Walmart, which is among the most visionary retailers, released its proprietary generative AI tool, My Assistant

But despite its tremendous promise, CIOs continue to stress how they can leverage this transformative AI technology. Shaown Nandi of Amazon Web Services talks about the need for CIOs to “put a plan in place to incorporate generative AI” or else face the prospect of being “left behind in two to five years.”  

In that light, this blog aims to discuss the top challenges CIOs are facing and how they can overcome them.

Challenge 1 – Unstructured Data

It’s precisely Generative AI’s ability to work with unstructured data that makes it appealing to enterprises. This ability to extract insights from documents, emails, images, and phone and chat logs, means that organizations can address challenges across multiple use cases like customer service and marketing. 

Effectively, Generative AI can “pull” data from multiple data sources, thus enabling organizations to access more content. However, one challenge is the quality of the unstructured data. Most LLMs are only as accurate as the data fed into them. 

Besides, with data stored in multiple disconnected repositories, most organizations are unable to leverage Generative AI capabilities.

The easiest solution is to integrate disparate data sources so that generative AI tools can efficiently leverage the available content.

Challenge 2 – Human Factor  

In a report released in March 2023, Goldman Sachs outlined that AI-led automation can automate 25% of the current jobs in the U.S. The investment banking firm has further stressed that generative AI could replace over 300 million jobs in the U.S. and Europe. 

This poses a serious challenge for CIOs as they need to consider the human resource factor. To complicate the matter further, they are often at the forefront of leading their organizations through AI-induced business disruptions. 

With the focus on upskilling, the current workforce needs retraining to work with generative AI tools. Besides training and upskilling, here are some effective measures that CIOs should take to address workforce-related challenges:

  • Facilitate collaboration among teams to leverage generative AI capabilities

  • Offer valuable insights into the benefits and risks of generative AI

  • Communicate to executive teams about the new jobs and opportunities generated by generative AI

Challenge 3 – Business Disruption  

Generative AI can solve complex problems faced by enterprises. According to McKinsey, generative AI can improve retail and consumer packaged goods sector productivity by 1.2% to 2% of annual revenues. Companies that don’t adopt generative AI face the risk of lagging behind their competition. Several companies are already losing market value with the sudden disruption caused by generative AI. 

However, it can also disrupt existing business processes — more than earlier technologies. What makes generative AI more challenging for CIOs is the rapid pace of its development and innovation. 

CIOs and business leaders must adopt generative AI into their production systems at the earliest. Additionally, CIOs must gain complete knowledge of this technology to guide or advise other employees.

Challenge 4 – Business Use Cases  

A recent Foundry survey ranked generative AI among the top five emerging technologies for investment by IT decision-makers. It is estimated that, by the end of 2033, the global economic impact of generative AI across all lines of business functions can be close to $10 trillion.

Also, in May 2023, IDC surveyed the use cases of generative AI that are most important. The survey found that 70% of the respondents are actively working on prioritizing their use cases or applications. That said, companies need their CIOs to prioritize “ideas” on how to use this AI technology for their benefit.

This requires CIOs to have a clear roadmap on how and where to implement generative AI across business functions. While doing that, they need to account for the technology’s maturity, data privacy concerns, technical resources required, the interdisciplinary nature of the technology’s implementation, and more.

Be it to improve productivity or reduce costs, they need to align their objectives before choosing the right technology to achieve them.

Challenge 5 – Data Security and Privacy  

A recent CIO survey revealed that 52% of organizations have security concerns associated with generative AI. This was followed by “complexity” (39%). Likewise, according to a Salesforce survey, 71% of IT leaders are concerned about generative AI introducing new security-related risks to their data. 

With the widespread use of generative AI tools, organizations are understandably wary about data privacy issues that could expose their proprietary information. For example, as per a recent analysis, 6% of employees were found to have posted sensitive data into generative AI tools. In the same vein, Samsung Electronics faced the “accidental leakage” of internal source code in ChatGPT.

Indeed, CIOs and business leaders need effective strategies to address data security and privacy concerns.

Overcome These Challenges with Recode

Without proper technical expertise and support, CIOs can find it challenging to leverage the capabilities of generative AI. This is where an experienced technology partner can make a difference.

At Recode Solutions, we enable our customers to leverage business value from their AI investments. Here are some reasons why you should consider partnering with us:

  • Expertise in AI-led automation that helps unearth opportunities for automation

  • Data analytics offerings, including data mining, consulting, and integration services

We can help you successfully embark upon AI-powered digital transformation. Contact us today for more information!

Author: Recode

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