The Gen-AI catalyst to Digital Transformation

According to McKinsey research , generative AI has the potential to add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases that were analyzed. Given that the United Kingdom's entire GDP in 2023 is estimated to be $3.168 trillion , the impact of the GenAI boom is likely to resonate throughout the world as the technology matures.

Although the impact of generative AI will be vast, the optimization of digital transformation processes for businesses is likely to transform the scaling process throughout virtually every sector.

While the influence of GenAI within digital transformation could see smaller use cases emerge over the coming years, in the future, it's likely to be a driving force behind the scaling process at enterprise level.

Today it's around optimization within a function. Over time we'll create business and value growth by looking at how those decisions interact with each other to create more value together. We'll see a shift to macro use cases, connecting silos and helping drive more business intelligence on how we connect decision making, sales to marketing to pricing to supply chain.

Let's take a deeper look into how generative AI will change digital transformation in the future to allow more businesses to scale efficiently:

Unlocking the potential of data.

Data forms the cornerstone of digital transformation, and this makes generative AI a valuable asset in accessing the potential of the data that can take enterprises to the next level.

Crucially, generative AI can take masses of unstructured big data and use it to make quantifiable and tangible insights that can grow businesses and their operations.

This includes using generative AI to create synthetic data that augments real-world source data, which can help when companies do not have enough material upon which to train machine learning models, or when confidential or sensitive data cannot be shared due to privacy concerns.

When it comes to digital transformation, this access to tangible data can offer unprecedented levels of insight into growth strategies that would otherwise be inaccessible or built on unreliable forecasting.

Through the GenAI boom, gone are the days of data warehouses. Instead, we're entering the era of the data lakehouse: achieving synergy between machine learning, business intelligence, and predictive analytics to gain unprecedented access to all types of structured, unstructured, and semi-structured data cost-effectively.

Embracing the CX boom.

The low-cost automation of business intelligence offered by generative AI can help to develop new strategies across a series of processes.

For instance, let's take a look at how multinational companies can utilize this revolutionary technology in optimizing measurable processes in the field of customer service. Innovations like the Pathways Language Model (PaLM), developed by Google Cloud, offer the ability to incorporate generative AI in conversation, dialogue design, modeling, architecture, and chat management.

PaLM can be used as a means of undergoing digital transformation to upgrade the customer experience (CX) models within businesses while retaining human specialists to step in when the AI is challenged with a complex or unusual task.

Furthermore, businesses will have the ability to utilize data from AI interactions with customers to develop more comprehensive insights into product demand, recurring pain points, and to analyze customer sentiment towards certain products or services.

The rise of the Large Language Models (LLMs) that are intrinsic to generative AI can provide more comprehensive help across a number of key industry practices, especially in places where digital transformation can be an unfamiliar proposition.

For instance, the hospitality industry suffers from an over-reliance on legacy systems that can stand in the way of digital transformation. When it comes to online ordering for restaurants, decision-makers often stick with existing systems and opt to add new pieces of technology on top of their legacy frameworks.

Over the long term, this approach can make it difficult to fully modernize and achieve seamless integration.

Specialist LLMs can make the digital transformation process more seamless. Today, there are already 14 LLMs aside from the world-renowned ChatGPT. For businesses that have large customer data sets, it's possible to tap into proprietary LLM platforms like Databricks Dolly, Meta Llama, and OpenAI, or to build their LLM from the ground up.

Given that machine learning programs can learn, conform, and build their understanding of business processes on the fly, they can serve as a key solution that requires relatively little time and effort to program. As the technology continues to evolve, training LLMs will become even more seamless.

Generative personalization.

Let's look deeper into how generative AI can deliver efficient digital transformation by continuing our exploration into restaurant use cases.

Crucially, generative AI can help to tailor the dining experience for customers in a way that significantly improves the quality of in-house or takeaway eating. This is achieved by GenAI models analyzing data like guest preferences, dietary restrictions, past orders, and behavior to offer personalized menu items and even recommend food and drink pairings.

Generative AI will even be capable of using available datasets to generate offers on the fly as an instant call-to-action (CTA) if it deems an online visitor isn't yet ready to convert their interest into action.

We're already seeing leading global restaurants announce the implementation of generative AI for their processes. In December 2023, McDonald's announced a global partnership with Google Cloud, with the incorporation GenAI technology set to provide more insights into kitchen performance to minimize disruptions and simplify workflows.

"We see tremendous opportunity for growth in our digital business and our partnership with Google Cloud allows us to capitalize on this by leveraging our size and scale to build capabilities and implement solutions at unmatched speeds," notes Brian Rice , executive vice president and global CIO at McDonald's. "Connecting our restaurants worldwide to millions of data points across our digital ecosystem means tools get sharper, models get smarter, restaurants become easier to operate, and most importantly, the overall experience for our customers and crew gets even better."

Looking deeper into the content personalization credentials of generative AI, businesses of all scales will soon have the power to cater to specific customer segments, leveraging data to generate focused, relevant, and engaging content in the form of emails, ads, and product recommendations. This will foster stronger engagement rates and higher volumes of lead generation.

Seamless integration on the horizon.

Generative AI became the technological buzzword of 2023 (and continues well into 2024), and for good reason. However, there will be many hurdles to overcome in the development of the technology before it drives widespread digital transformation.

Regulatory hurdles may be tricky to overcome due to issues in how AI programs can handle private data and utilize intellectual property (IP). Quality shortcomings could also cause issues in governance among early LLMs, and we've seen plenty of cases where language models "hallucinate" when dealing with unusual queries.

Once these lingering issues are overcome, generative AI could emerge as the driving force in the race for digital transformation across countless industries. For the many sectors where staff aren't fluent in digital processes, the ability to automate operations could improve CX models on a comprehensive level.