Telecom & Technology Consulting
“Digital transformation” can be a misleading term. Many believe the concept has a definite beginning and end (whenever that may occur), but the transformation itself is often an ongoing process. New technologies and shifts in the market force organizations to adjust their digital transformation initiatives. Artificial Intelligence (AI) is the latest tool that must be folded into those projects.
And for good reason. Generative AI and other large language models (LLMs) are affecting (or soon will be) every corner of the today’s enterprises: Sales, marketing, product development, customer service, operations, procurement, everything. Accordingly, CIOs and CTOs must anticipate how their digital transformation budgets can accommodate the need for AI and LLM tools.
There’s no magic formula for balancing AI/LLM deployment with budgets. The task for tech leaders is to get creative and discover how they can accomplish more with less. To that end, give priority to digital transformation initiatives that are most likely to create new revenue streams. So as you move forward with AI and LLM, develop the same type of prudent strategies you would employ for other key business initiatives.
On a related note – from a tactical perspective – be sure to clean and prepare your data for private LLMs. Keep in mind that generative AI functionality will boost the value of the unstructured data located in your documents and other content types. You can’t predict how generative AI may disrupt your business, but it’s smart to take proactive measures around centralizing and purifying data for use in LLMs.
This is a critical step for any organization undergoing a digital transformation. The reality is that users across every department are craving to use generative AI to enhance their productivity. And that can only occur when CIOs and CTOs foster access to generative AI tools, and give data science teams the license to design LLMs specifically for the organization’s unique needs.
But the development of LLMs can’t be arbitrary or driven by mere user demands – it requires a strong business case, which in turn necessitates funding. Training LLMs can bring a hefty price tag, and the results aren’t yet consistent. Based on the current LLM environments, leaders should be sure to monitor usage costs, and work towards improving results incrementally over time.
Digital transformation has always been viewed as a way to improve customer support. Adding AI into the mix can multiply that improvement. Specifically, generative AI enables customer support personnel to more accurately resolve customer issues in less time. Many enterprises are leveraging ChatGPT4 and LLM to optimize customer support, especially for automating tasks and analyzing massive amounts of unstructured data.
Enhancing customer support represents an immediate way to gain short-term ROI from LLMs and AI search capabilities. And once the IT department can centralize data and implement a private LLM, more growth opportunities will appear such as better lead conversion and a more efficient onboarding process for human resources.
However, to realize long-term success, management must clearly communicate how the LLM governance model works. Employees may naively use proprietary or other confidential information for their prompts. To avoid this problem, leaders should provide unambiguous policies about how to use AI and LLM tools in an approved manner.
To accomplish that goal, tech leaders should partner with multiple departments to not only create a viable governance policy, they must agree on a policy that supports experimentation. To begin, CIOs and CTOs should assess how ChatGPT and other generative AI tools can affect software development. They should also collaborate with marketing leaders to determine how generative AI can boost the effectiveness of content creation, lead generation, email marketing, and other marketing activities.
With all of its capabilities to improve quality and efficiency, AI also the power to enhance how organizations make decisions. This idea is vital to consider, as the business landscape has predominantly become one based on making data-driven decisions. Generative AI offers entirely new possibilities, which allow leaders to get answers in literally a blink of an eye.
But the questionable accuracy of those answers, as well as unintended bias, can cause big problems – ones that have long-term ripple effects. In that light, we strongly recommend that you don’t completely abandon the human factor. We still need humans to interpret if specific prompts lead to the best answers delivered by generative AI. Human intelligence is still the best way to ensure that we have the facts right, and that our ultimate courses of action are ethical and socially responsible.
Indeed, generative AI and LLM models should never be seen as a wholesales replacement for humans. Instead, think of AI and LLM as key advisors that can supplement the decision-making process. By taking a balanced approach, these new technologies will peacefully co-exist with your digital transformation – and hopefully make that transformation more fruitful than you had initially imagined.
