The Big Business Rethinking - AI Digital Transformation as The New Innovation’s Paradigm

After hundreds of conversations with business leaders from companies of all sizes, I noticed how many of them are still downplaying the real impact of AI on their businesses.

The advent of AI has had a seismic impact on all business functions across all industries. It is the single best opportunity to innovate both progressively and disruptively that we have had in the last decades.  If they don't react on time, many leading organisations will be challenged and dethroned by newcomers that are faster to innovate and disrupt their business models.

Generative AI technology, in particular, has been responsible for a great part of this shift in balance. LLMs became widely available seemingly overnight, propelled both by top technology companies and highly funded new players racing each other to come up with the best product.
‍

New tech capabilities easily implementable

With AI, organisations have access to new capabilities,  which go beyond traditional automation. These are empowering businesses to leverage AI for sophisticated tasks that were once considered far from the reach of machines.

^{Advanced Text Creation} 

In the past, seeing a chunk of text was a good indication that a human had been involved in creating it. Generative AI has completely changed this: it  now excels at creating human-like text, enabling businesses to automate the production of various content types, from product descriptions to customer emails and research summaries. This ensures content is relevant, personalised, and consistent with brand messaging._‍

^{Speech-to-Text and Text-to-Speech} 

Improvements in AI-driven speech recognition and synthesis offer near-human accuracy, making it easier for businesses to transcribe audio or create natural-sounding voice overs for automated services and marketing content.

^{Image and Video Generation}

AI can now generate high-quality images and videos based on textual descriptions. This capability reduces the need for traditional production methods, allowing for faster and more cost-effective content creation in marketing and product design.

^{Natural Language Understanding and Processing}

Enhanced natural language understanding allows AI to better interpret and respond to human language. This is particularly valuable in customer service, sentiment analysis, and automatic translation, enabling more accurate and context-aware interactions.

^{Multi-Modal Content Creation}

AI now supports the creation of integrated content across text, images, and audio, streamlining the production of cohesive marketing campaigns that require minimal human intervention.

^{Real-Time AI Translation}

AI-driven real-time translation has become more accurate, facilitating smoother cross-language communication in global business operations, customer service, and content localization.

^{AI-Driven Design Automation}

AI can generate design assets like logos and website layouts based on basic inputs, accelerating the design process and allowing for rapid prototyping without extensive human involvement.

^{Enhanced Data Analysis with AI-Generated Reports}

AI can automatically generate detailed reports from large datasets, highlighting key insights and recommendations, which helps businesses make informed decisions more quickly.

^{Synthetic Data Generation}

AI can create synthetic data that mimics real-world datasets, enabling businesses to train machine learning models even when real data is scarce or sensitive, particularly useful in industries like healthcare.

"Much of the impact of this technology shift is owed to the simplicity of outcome generation. Generative AI enables us to generate and transform content without the need of software programming involved.  Prompts and instructions given in natural language do the magic.”

As a consequence of AI’s advanced capabilities, it is estimated that as many as 80% of business tasks could be enhanced or automated. The complexity of implementation is limited and the dimension of the impact in each task is incrementally bigger, as it evolves with every AI technology upgrade released.

Many of the tasks based on human reasoning and manual execution that we currently perform will make no sense anymore and will either disappear or be transformed.

Many of the business processes that were  programmed in the past, and many of the software tools teams currently use, are already obsolete. What is more, they are already hindering organisations’ ability to increase value to customers and employees.

For  example, migrating code from one programming language to another is something that can be done with a prompt and the original code input, without the need of any manual coding. The outcome provides a high level of accuracy, saving a significant amount of hours in development time. That high level of accuracy differs depending on the programming language, but in many cases it is equal or higher to what a human could produce.

AI is still evolving and its outcomes are in many cases far from perfect. For some use cases, outcomes directly generated with AI through simple prompts are not yet useful  for business purposes. For others, outcomes offer a high level of quality that make them suitable to enhance or even replace outcomes currently generated by humans.

‍

The New Paradigm of AI Digital Transformation

AI digital transformation is a must for any business. To remain being competitive in five years time, companies now need a strong generative AI strategy. Even if a company has a large  market share, they won’t be leading their industry in three to five years if they don’t tackle AI digital transformation now.

^{Is AI Digital Transformation any different from Digital Transformation?}

In general terms, when we talk about AI adoption and digital transformation, we are talking about the same concept. The difference lies in the scope of such transformation.

For the companies taking their first steps into digital transformation, the difference between the two concepts will go through almost unnoticed because incumbents and newcomers will be evaluated at the same level, focusing on the problem that they want to solve.

The big change comes for those companies that were already digitally mature according to technology standards previous to the current AI wave.

“The concept of digital maturity has been reset by the volume and capabilities of the new AI developments. Leading digital organisations are back to the cradle and will need to work back out their way to maturity.”

For them, AI digital transformation has a different scope as for those taking their first digital steps. Leading digitally mature companies need to re-evaluate each of their operational and customer processes in terms of AI transformation and make AI implementation decisions based on the impact and customer value brought by the new AI capabilities. The task may look daunting, but the gains are enormous.
‍

AI Business Impact it’s Already Telling the Story

The difference in impact between an AI sceptical company and an AI leading organisation is already tangible. Costs savings in the double digits and revenue growth on several business functions, growing cash flows, and in some cases, several points in gross margins improvements.

^{AI-First Organization and AI Digital Transformation}

A concept we will start hearing very often is the concept of AI-first organisation.

The concept began gaining prominence around 2016, as leading tech companies like Google and Microsoft began to highlight AI as central to their future plans. For example, during Google's 2017 developer conference, CEO Sundar Pichai revealed that the company was transitioning its focus from "mobile-first" to "AI-first."

Different articles such as Harvard Business Review’s Karim R. Lakhani’s “Competing in the Age of AI” and Rajesh Kandaswamy’s “Building an AI-first company - Introduction” talk about what means to build an AI-first company.

AI-first organisations place artificial intelligence at the very centre of their business strategy and operations. They rely heavily on AI to drive innovation, streamline processes, and make informed decisions. Rather than viewing AI as just another tool, they treat it as a fundamental component that shapes their entire business model.

Key characteristics of an AI-first organisation include:

These characteristics enable AI-first organisations to not only optimise their current operations but also position themselves for long-term success in an increasingly digital world.

It’s undeniable that AI Digital Transformation requires an AI-First business mindset. On the other hand,  I  must be alert of the risks of wrongly placing AI as the main goal of the organisation itself.

A similar opinion was shared by professor Oguz A. Acar on Harvard Business Review a few months ago.

If you lose sight of AI as a means to solve "real" organisational and customer problems, satisfy your customers and employees or achieve major process optimizations, you could run into big trouble. That’s why you must set up  a necessary connection between your main business goal and metrics and AI decision-making.