The Future of Disruptive Tech

Disruptive Technologies in Business: GenAI & Knowledge Work

In the fast-paced world of business, staying ahead means embracing the cutting edge. Enter Generative Artificial Intelligence (GenAI) — the game-changer that’s redefining how we work. Imagine a workplace where mundane tasks are automated, leaving you free to flex your creative muscles and tackle the more complex challenges.

GenAI undeniably holds immense potential for reshaping how organisations operate. In this guide, we will delve into how GenAI is redefining the realm of knowledge work, the vital steps for its successful adoption, and the strategic advantages it offers. Join us as we explore the future of disruptive tech and its profound impact on business productivity and efficiency.  

What is Disruptive Technology?

The term ‘disruptive tech’ refers to a piece of technological innovation that has the potential to radically alter a traditional way of working. This trickles down from global markets to industries, companies and consumers, leading to changes in the economic landscape in a short period of time. Three examples of disruptive technological innovations that have altered human communication as a whole include:

• The Internet created a global network for transferring information, becoming even more prevalent once they left the office and entered our homes, when access was democratised, and with it, access to information.
• Mobile Devices brought us the capability to reach anyone on the go. Though mobile phones today have nothing to do with what they were in their origins, even back then, they altered human communication and our day-to-day lives.
• Social Media is the undisputed winner when it comes to altering human communication. We grew up in a world where social media didn’t even exist; now, it’s fundamental in human interactions.

We may now take these for granted, but at one point, they seriously transformed life as we know it.  

The Race for GenAI Adoption

We’re currently living in the fourth industrial revolution, marked by digitalisation. One of the biggest landmarks of this fourth industrial revolution is GenAI, a disruptive technology that is rapidly impacting global markets.

Companies such as Nvidia, the main microchip manufacturer for running and training GenAI models, recently became the most valuable company in the world. And today, all types of businesses are taking part in the race for GenAI adoption. This will determine the future of many of the businesses and industries we know today.

A full and proper implementation of GenAI will also lead to cost savings, as organisations are able to free up resources and have employees focus on more strategic tasks that will lead to new value creation. A strategy that focuses on both cost savings and value creation ensures a sustainable competitive advantage. While cost savings improve the bottom line, value creation drives top-line growth.

Adoption of GenAI technologies can be highly beneficial, especially in organisations that rely heavily on Knowledge Work. Nevertheless, a proper strategy and alignment with business objectives and goals are paramount to ensure the initial investment (that can be elevated) will drive cost savings, value creation, increased operational efficiency and competitive advantage.  

What is a Knowledge Worker?

A knowledge worker is someone whose labour consists of intellectual tasks that involve the cognitive processing of information. With disruptive innovations come changes along the chain of command and production. Before the internet, computers, and mobile devices, the majority of labour could be categorised as manual labour, but this has changed. A large proportion of workers are now in an office or set to work from home. Most of that labour consists of knowledge-based jobs, which are related to:

• Word Processing: like writing lines of code or creating sales materials
• Image Processing: for example, when creative teams develop marketing campaigns that require visual support
• Number Processing: if you’re involved in accounting or payroll management
• Sound Processing: as somebody handles phone calls with customers or even classifies audio files to feed a Large Language Model (LLM).

In the modern office, very few employees perform manual labour (unless you’re pouring coffees for your boss or printing copies). We could say then one of the main characteristics of knowledge work is it requires some level of intellectual preparation and specialisation. Within knowledge work, there are two main types of tasks, structured and unstructured tasks.

• Structured Tasks: include those with clear procedures and inputs to produce outputs from, like a person from the financial department sending out monthly payrolls
• Unstructured Tasks’: procedures are not as clearly defined, such as a designer working on a website’s UX.

Computers have always been very good at performing structured tasks, and thanks to GenAI they’ve become quite helpful at performing unstructured tasks. GenAI is blurring the lines between exclusively human work and work that machines can do.

How is GenAI Impacting Knowledge Work?

Disruptive technological developments like LLMs, ChatGPT, and DALL-E make tasks like writing, coding, and image generation less challenging. These tools provide human workers with cognitive boosts. Taking weight off particular workloads (for example, automating email writing) allows knowledge workers to focus on more creative and complex responsibilities.

One example of a large company using disruptive technology is Bank of America with its GenAI assistant Erica. In six years, this chatbot has helped more than 42 million clients answer 800 million queries.

In the Healthcare industry, GenAI has created 3D models of specific proteins thus accelerating the development of drugs for treating conditions like schizophrenia and depression.

Elastacloud, our latest acquisition in data and AI, integrated their GenAI solution Knowledge Miner into one of their clients’ Customer Service division. This department had been struggling while on the phone with customers, as employees had to quickly find information related to a person’s query. The amount of time needed to locate the correct documents and scan through them led to customer dissatisfaction.

The GenAI solution provided the company with a custom search interface which allowed workers to search through vast numbers of documents with little effort, and to ask natural language questions that would lead to direct answers. Customer Service Agents now save several minutes per call and the company reported improvements in delivery times, customer satisfaction, and cost of administration.

Now that we have a clear view of GenAI’s impact on knowledge work, what can organisations do to leverage this tech?  

Introducing the WINS Framework

To kick your GenAI journey off, it is important to first understand your organisation’s current stance in adoption. Unpacking and acknowledging your industry’s position will help you understand how urgent it is for your firm to adopt GenAI technologies, and how ready you are for this journey. It’s crucial for organisations to ask themselves these two questions:

• How digitised are our WINS inputs today?
• How much of our cost base is made up of WINS work?

WINS stands for Words, Images, Numbers, and Sounds, and these are an integral part of knowledge work, the labour that Gen AI will transform in the short run.

A recent review published by the Harvard Business Review outlined their research analysing over 3,000 GenAI Practitioners and how the WINS Framework can help leaders identify how vulnerable their organisation is to changes from a new technology they are thinking of adopting.

Having your eye on the latest tools is not enough to achieve GenAI’s full transformative potential on WINS work. An adaptable and AI-ready environment is a must for an organisation looking into Gen AI’s capabilities. This leads us to two of the main aspects of adoption: digitalisation and general readiness.

Digitalisation means converting information into a digital format, so companies can ingest their data into the models they’re using. This requires a data strategy and proper data management, involving standardised data collection, storage, and access; investing in data cleansing and enrichment tools to improve data quality; and establishing centralised data repositories to streamline accessibility for AI applications. Taking care of other challenges like integration of legacy systems and scalability and infrastructure is crucial as well.

General readiness refers to broader organisational preparedness, and this means addressing issues like leadership buy-in, employee training, and ethical considerations surrounding AI use and management strategies. It also relates to having a data-driven approach. Companies that put data first are capable to make more informed decisions based on analysis and actual numbers.

The Future is Now

Today, adopting GenAI is no longer just an option; it’s a strategic imperative. The influence of GenAI on knowledge work is transformative, offering unprecedented opportunities for efficiency, creativity, and competitive advantage.

Now is the time to put this knowledge into action. You could start by assessing your organisation’s digital readiness and pinpointing areas where GenAI can make the most impact. Why not engage your team in discussion sessions to get everyone onboard? And don’t forget; the fun part lies in experimenting with these cutting-edge tools and watching your business processes transform. Embrace the future, and let GenAI take your organisation to the next level. The possibilities are endless, and the time to act is now.

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