Business impacts of GenAI: advantages and pitfalls

August 2023  |  COVER STORY | BOARDROOM INTELLIGENCE

Financier Worldwide Magazine

August 2023 Issue

Down through the ages, mankind has been given to invention and experimentation. From the earliest Stone Age tools through millenniums of exploration and discovery to today’s sophisticated technologies, the desire to push boundaries has been strong and progress certainly spectacular.

Over the past decade, one of the most sophisticated technologies to have emerged is that of artificial intelligence (AI) – an extraordinarily powerful and rapidly evolving technology that is fundamentally transforming the world and all our lives along with it.

One evolutionary strand of AI that is certainly having a major transformational impact on global human creativity and productivity at this time is generative artificial intelligence (GenAI).

As defined by Azumo in its 2023 ‘The Power of Generative AI: A Complete Guide for Business’, GenAI is a type of AI that focuses on creating new data, such as images, text and sound, that is realistic and similar to what a human might produce, rather than analysing and processing existing data, which is the focus of traditional AI, and typically used for tasks such as classification, regression and clustering.

“GenAI technologies have ushered in a new paradigm in business, pushing the boundaries of what is possible in creative tasks, predictive modelling and personalisation,” says Shivam Bawa, head of partnerships at Azumo. “It is being adopted faster than many other emerging technologies due to its versatility and transformative potential. It is ushering in a new era of innovation, opening opportunities in sectors ranging from retail to healthcare, from automating content creation to developing more targeted and personalised user experiences.”

A demanding technology in and of itself, GenAI requires significantly more computing power and data than traditional AI, due to the complex algorithms and models involved in creating new data – a process achieved by training algorithms on large data sets to identify patterns from which the algorithm can generate new data that fits the same patterns.

“Until now, AI has largely been about perception, understanding and getting insights from data,” adds Carlo Ruiz, head of EMEA AI data center solutions at Nvidia. “GenAI can help produce things like poetry, images and music that previously required human effort to create. These systems use graphics processing units (GPUs) and AI software to train deep learning models on massive data sets to create an AI-generated output with intrinsic value.”

Types of GenAI

Like any new technology, various types of GenAI exist, and these iterations, as noted in the Azumo guidance, are outlined below.

Generative adversarial networks (GANs). GANs are a type of neural network that consists of two parts: a generator and a discriminator. The generator creates new data, while the discriminator evaluates the quality of the data. The two parts work together in a feedback loop to create high-quality data that is similar to what a human might produce.

Variational autoencoders (VAEs). VAEs are a type of neural network that are used for data compression and reconstruction. VAEs can also be used for generative tasks by sampling from the learned distribution to generate new data.

Recurrent neural networks (RNNs). RNNs are a type of neural network that are designed to process sequential data, such as text or speech. RNNs can be used for generative tasks by training the network to predict the next character or word in a sequence.

Underpinning the capabilities of GenAI, as outlined by the World Economic Forum (WEF), are three main elements: (i) massive memory and pattern recognition, with the capability to connect distant concepts or ideas and draw inferences; (ii) low or no code requirements, which significantly reduces the premium on coding skills; and (iii) an absence of logic, since it makes predictions based on massive amounts of training data, with significant consequences for its applications to work.

GenAI in business: advantages

GenAI is having a far-reaching impact across the business landscape, ranging from content creation automation to supply chain optimisation and improved customer service – empowering companies to make well-informed decisions, optimise operations and augment profits.

“GenAI offers immense advantages to businesses,” contends Mr Bawa. “It provides the ability to generate new content rapidly, design innovative products and improve decision-making processes, thereby increasing efficiency and cost savings.”

And though a nascent technology, to date, business adoption of GenAI has been extensive. According to IBM’s ‘2022 global AI adoption index’, 35 percent of companies have incorporated GenAI into their operations, enabling them to solve complex problems with ease by utilising GenAI tools such as ChatGPT to analyse vast quantities of data at a speed far beyond that of traditional analytical methods.

Supporting IBM’s findings is a recent KPMG survey, which found that almost two-thirds of the US executives it surveyed believe GenAI will have a high or extremely high impact on their organisation in the next three to five years, far above any other emerging technology.

Moreover, when it comes to the impact of GenAI at the enterprise level, 78 percent of respondents said it will have a high or extremely high impact on driving innovation, followed closely by technology investment at 74 percent and customer success at 73 percent. However, respondents believe the greatest transformational impact will be on R&D product development and operations.

“There is no doubt that GenAI could be truly revolutionary for both businesses and society,” asserts Todd Lohr, US technology consulting leader at KPMG. “There is a true first-mover advantage with the pace of GenAI innovation. Winning organisations will establish their competitive advantage by taking decisive action now, while ensuring they are taking the proper steps toward mitigating risk and implementing responsible AI.”

In terms of GenAI’s impact on labour and productivity, Goldman Sachs, in its ‘The Potentially Large Effects of Artificial Intelligence on Economic Growth’ report, suggests that the technology could raise annual US labour productivity growth by just under 1.5 percentage points over a 10-year period following widespread business adoption. The report also states that GenAI could eventually increase annual global GDP by 7 percent, equal to an almost $7 trillion increase in annual global GDP over a 10-year period.

ChatGPT

While there are numerous GenAI models on the market, including Bard and Bing, it is ChatGPT that is undoubtedly having the greatest impact on businesses and their plans for the future.

As stated by PitchBook in its 2023 ‘Emerging Tech Future Report: Generative AI’, ChatGPT represents the evolution of AI into an easy-to-use consumer-focused product with immediately apparent return on investment. The technology enables even the most unskilled worker to conduct advanced AI-powered research through a simple chat-based interface.

For enterprises, the maturation of transformer-trained large language models (LLMs) could have broad implications for many operational functions, including customer support, analytics, research & development and software engineering, to name just a few – potentially driving a step-function lift in productivity and efficiency in ways that could transform organisational structure.

“ChatGPT was a watershed moment that has focused world attention on GenAI,” asserts Mr Ruiz. “Tens of millions of people are using it for many different purposes and have found it incredibly useful, and we expect that such GenAI is going to have a monumental impact on technology.

“Businesses, consumers and governments are excited about the potential of ChatGPT across many domains,” he continues. “We see a huge opportunity in helping companies create ethical GenAI applications that produce accurate results.”

GenAI in business: pitfalls

As well as the considerable advantages proffered by GenAI, the technology also brings potential pitfalls, chief among them ethical issues surrounding data privacy, security, policies and employment dynamics. GenAI technology can also potentially produce a series of new business risks such as misinformation, plagiarism, copyright infringements and harmful content.

“Ethical concerns around content creation and authenticity also surface as GenAI can generate realistic but artificial content,” says Mr Bawa. “There is also the risk of GenAI technology being misused for producing deepfakes or spreading disinformation. In addition, the computational power required for sophisticated GenAI applications can be substantial.”

Business preparedness for GenAI is also an issue. The KPMG survey found that fewer than half of respondents believe they have the right technology, talent and governance in place to successfully implement GenAI. Respondents stated that they anticipate spending the next six to 12 months focused on increasing their understanding of how GenAI works, evaluating their internal capabilities and investing in GenAI tools.

“Businesses show varying levels of preparedness for the widespread adoption of GenAI,” observes Mr Ruiz. “To navigate its impact, they should prioritise understanding AI’s potential, invest in AI talent, align strategies with business objectives, assess data readiness, address ethical considerations and foster an innovative culture.

“By embracing AI education, building multidisciplinary teams and developing data infrastructure, businesses can harness GenAI’s positive impact on operations, while also proactively addressing potential challenges such as ethical implications, workforce transitions and regulatory compliance,” he continues. “Strategic planning and proactive adaptation are key to unlocking the benefits of GenAI and staying competitive in the evolving AI landscape.”

In addition to the potential pitfalls involved in adopting GenAI, there are also pitfalls associated with not adopting the technology (though no technology should be adopted purely for adoption’s sake) – in the main, the likelihood that non-adoption will lead to a business being outfoxed by its competitors.

Regulation

A key issue with the rapid expansion of GenAI is regulatory concerns, with the general lack of oversight in this area prompting calls by AI luminary Sam Altman, chief executive of OpenAI (creator of ChatGPT), as well as global institutions such as the World Health Organization (WHO), among others, for a regulatory roadmap for AI, encompassing GenAI.

“AI, like all technologies, must be designed, deployed and continually assessed in ways that are safe and responsible,” adds Mr Ruiz. “We believe that every organisation must adhere to the principles of trustworthy AI – meeting regulatory compliance using responsibly sourced data sets and utilising guardrails to ensure safe and accurate output.

“It is important for regulators to understand existing laws and the potential impact of any proposed legislation and get industry input,” he continues. “We are encouraged by efforts from regulators to not approach AI systems monolithically.”

Certainly, as the race to develop more powerful GenAI like ChatGPT accelerates, the pressure on regulators to draft new rules that could set the global benchmark to address privacy and safety concerns intensifies. These regulations will be tasked with controlling a technology that many believe could upend the way societies and businesses operate.

“The ascension of GenAI will undoubtedly influence the regulatory landscape,” adds Mr Bawa. “It may lead to stricter data privacy laws, new rules around intellectual property as it pertains to AI-generated content and legislation to curb the misuse of AI for generating disinformation. These potential changes may heighten the complexity of regulatory reporting for businesses, pushing them to demonstrate their ethical and legal usage of GenAI and AI at large.”

Profound impacts

Across the board, the consensus is that GenAI will transform a range of sectors and industries, enabling greater efficiency, personalisation and innovation. At the same time, businesses must also address ethical, privacy and regulatory considerations to ensure responsible and beneficial implementation of GenAI technologies.

“We anticipate GenAI having a profound impact on businesses in the coming years in ways that are currently difficult to predict,” contemplates Mr Ruiz. “Leaders now realise that GenAI can boost productivity and efficiency, and are racing to explore ways that the technology can be harnessed to advance their businesses and better serve their customers.

“GenAI is also going to put more power in the hands of more people than ever before, because previously there were many challenges that could only be solved by engineers and computer programmers,” he concludes. “Now, with GenAI, we have a new computing paradigm. It is no longer necessary to learn C++ or Python; rather, anyone can type what they need into a prompt and computer software will do the rest.”

Impacting many segments of society and industry, GenAI is expected to accelerate innovation like never before. “Over the next three to five years, we can expect GenAI to play a central role in business operations, particularly in areas requiring innovation, creativity and personalisation,” concludes Mr Bawa. “GenAI will also drive more nuanced customer experiences and enable faster decision making, transforming the business landscape in unprecedented ways.”

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Fraser Tennant