Future of Generative AI: Unlock Tomorrow’s Business Landscape

If you read today’s paper, you would be forgiven for thinking that AI was a brand-new technology. But in reality, it’s been around for years – just look at the Netflix recommender engine or Alexa. However, the emergence of Generative AI (GenAI) has moved the dial and made AI the household topic it is today.

This ‘buzz’ can largely be attributed to the significant potential GenAI presents across an almost endless range of applications. Within a few months of its launch research found that GenAI features stood to add up to $4.4 trillion to the global economy annually.

Its speed has also helped the technology to take centre stage. Whilst the advanced machine learning that powers GenAI enabled products has been decades in the making, since ChatGPT emerged in late 2022 new iterations of GenAI technology have continued to be released multiple times a month.

New tech developments typically go through these ‘hype’ cycles -we experienced the same with Big Data and even data science itself. But where GenAI differs is in the way in which it has passed into the mainstream consciousness, stimulating a lot of noise around the topic, and sustaining the ‘hype’ for longer than most other applications.

This presents a challenge for those businesses looking to implement GenAI technology. Not only is there no blueprint to follow,  it has also become increasingly difficult to separate the real from the perceived benefits. As we navigate the future of generative AI, the ability to discern and harness its true potential will become a critical skill.


The future of generative ai: GPT and Bard


So, what does Generation AI do?

The promise of GenAI is that of artificial creation. Drawing on vast quantities of data and inputs, models can produce content to fit a specific length, format, or topic. This breadth of uses makes it transformative but also almost impossible for guidelines to keep up. The challenge for leaders will be the governance and management of data – how they can safely use AI and protect customer and employee personal data?

And with every new use for AI comes a greater risk of misuse and more opportunities for cybercrime. So, for GenAI to fulfil its potential there needs to an accompanying discussion around how to regulate that innovation.

For example, as Generative Visual AI becomes more advanced, the images and videos that it creates will become less easy to distinguish from reality. This could lead to issues such as deepfakes and disinformation. However, steps are already being taken to combat this. The European Union's AI Act, for instance,  now requires companies to watermark AI-generated text, images, or video.

What is involved in the future of Generative AI ?

It’s clear that GenAI technology will have a big impact on the way we live and work. Octopus Energy, the tentacled clean energy provider, reports that 44 per cent of its customer service emails are now being answered by AI. Clearly, there is enormous economic potential but there are also factors that will determine how fast it will grow and in what direction.

The potential for businesses

Business uses of GenAI will roughly fall into four areas: customer operations, marketing and sales, software engineering, and research and development. But where previous waves of automation technology mostly affected physical work activities, the future of generative AI is likely to have the biggest impact on knowledge work such as activities involving decision making and collaboration.

Of course, some industries will gain more than others. Due to GenAI’s ability to predict patterns in natural language and use it dynamically, professionals in fields such as education, law, technology, and the arts may see elements of their jobs automated much sooner than expected.

However, the outputs of GenAI will only be as good as the data that is put in. So, as mundane as it might be, companies must first establish comprehensive data governance strategies – ensuring data is not only being collected and stored properly but also of a high enough quality to be fed into AI software.


MIT generative AI week

Businesses must work to manage the hype – adoption will take time.

When it comes to integrating AI, it’s common to see businesses trying to run before they can walk. The buzz around the topic means that organisations feel as if they are fast falling behind and therefore want to skip to step six where they hope to see significant RoI and make exciting discoveries.

Managing the hype of AI is one of the biggest challenges faced by business leaders and data teams. Many are convinced that everyone else has got some fantastic AI running their organisation and that they are behind the curve whereas in reality most people are still talking about how they could use it.

In a recent study, 76 per cent of mid-large company IT decision makers felt GenAI would have a transformative impact on their organisation. But only 20 per cent of those surveyed have rolled out generative AI tools and training for staff. Moreover, just 9 per cent have established core use cases for generative AI.

iRobot co-founder Rodney Brooks also believes that hype could be causing leaders to ‘over-estimate’ GenAI’s capabilities. At MIT’s Generative AI Week , he stated that he is “most worried about researchers who may throw away decades of excellent work, just to jump on shiny new advancements in generative AI; firms that blindly swarm toward technologies that can yield the highest margins; or the possibility that a whole generation of engineers will forget about other forms of software and AI.”

The truth is that many businesses want to reap the benefits of AI – they just don't actually know which business goals AI will help them to achieve. Leaders need to consider AI as they would any other new technology - asking themselves questions such as, 'Will this actually help me to achieve X?' And then working backwards to determine what processes would need to be in place to make it possible.


GenAI literate employees

Educating the wider network of employees (not just tech teams) is crucial to widespread GenAI adoption. Terms like ‘Data Literacy’ have been floated for a while, and organisations need to roll out ‘AI Literacy’ programmes in the same way.

It’s essential to thoroughly train graduates all the way to executives by highlighting what AI is, why it is beneficial to the business, and what parts of the business it benefits. Not forgetting the potential harmful side of AI, too. The ‘hype’ needs to be managed, and CTOs, senior tech employees, data and digital leaders can help drive this.

Ensuring that all staff receive training is also crucial to managing the risk that comes with GenAI – such is the spread of misinformation. For the future of generative AI & your organisation, it's critical to keep a human in the loop, it will help to ensure that any outputs are both accurate and sense checked.

Physical, digital, and human resource

Whilst GenAI has enormous economic potential, large up-front investment is needed in physical, digital, and human capital to make the most of it.

In our recent salary survey, 47 per cent of respondents believe that AI and Machine Learning will have the biggest impact on the data market this year, whilst 26 per cent believe it will be availability of talent.

As organisations begin to set gen AI goals, we are already seeing a surge in new ‘AI’ job titles, such as AI Engineer – roles historically filled by data engineers or data scientists. And this is likely to continue in 2024. Indeed, we’re currently seeing more AI roles in the innovation space rather than regulation, but with the capabilities of Gen AI being realised, there will likely be a surge in regulation roles.

The Future of Generative AI: A shifting workforce

Forecasts show that GenAI could substantially increase labour productivity across the economy. To reap the benefits of this productivity boost, workers whose jobs are affected will need to be supported in re-skilling and shifting to other work activities. For example, if GenAI can be used to speed up the time-intensive manual work, such as compiling research, it could free up time for workers to take on higher level fulfilling tasks.

Ultimately, GenAI should be treated as just another tool in your box to help you to achieve business goals, rather than the solution to every problem.

This isn’t a unique circumstance; technology has been altering jobs since the industrial revolution. The key is establishing how to work with GenAI, not be at odds with it.


Looking for your next data role or keen to put your skills to good use in an innovative fast-paced sector? Get in touch with the team today.

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