Making Generative AI Work for You

ChatGPT has sparked the latest explosion of interest in the ‘omnipotent’ field of AI. Everyone is – from high school students to software programmers, C-suite executives to creative writers and designers – both curious and excited about the prospects of ChatGPT and apprehensive about its undefined implications.

The core technology behind ChatGPT is ‘generative AI,’ a category of AI that uses several types of large language models, networks and algorithms, to produce, manipulate or synthesise data. In simple words, it enables users to quickly generate/output new content, based on various inputs. Inputs and outputs include text, images, code, sounds, animation, 3D models, or other types of data. ChatGPT and Dall-E 2 (by OpenAI), Google’s Bard, Copy.ai, Midjourney, Lumen5 and InVideo are currently some of the most popular generative AI tools.

Why the hype? The ability of this technology to swiftly create something entirely new and which previously didn’t exist as well as produce highly realistic and complex content mimicking human creativity is the reason why generative AI has taken the world by storm.

According to a report by Grand View Research, the global market for generative AI tools is expected to reach $109.37 billion by 2030, growing at a CAGR of 35.6% from 2023 to 2030. Almost all leading tech players, including Google, Microsoft, Amazon, OpenAI and Nvidia, have launched their generative AI tools for the public and have received an overwhelming response.

Generative AI is poised to have an exponential impact on all major industries, from finance and education to tech, media, marketing and healthcare. You can ask ChatGPT, Bard or any other such tools to write a work anniversary speech of a specific word count; code or fix code in any programming language; create an outline and write an article on any topic; create a social media marketing plan promoting an event, or even produce an image of a pink shark in the River Indus – really, the sky (and your imagination) is the limit!

More ‘business-y’ generative AI examples include Nike’s NIKE ID, which allows customers to design their own shoes; Exscientia, an AI-based pharma model that can design new drugs more quickly and efficiently than traditional methods. Coca-Cola’s Masterpiece that brings alive the artwork of Van Gogh, J.M.W. Turner, Andy Warhol and Fatma Ramadan (among other artists) is a branding masterstroke, entirely created through GPT-4 and Dall-E. Gartner even predicts that by 2030, a major blockbuster will be released with 90% of the film generated by AI (from text to video), up from zero percent of such in 2022!

This rapid growth is being powered by a number of factors, including increasing demand for AI by industry, growing availability of large data sets and advances in hardware and machine learning algorithms.

How should business leaders respond? How can companies and leaders position themselves for success in this new age of generative AI? It’s crucial to start with a clear goal. Explore what results you hope to achieve by adopting generative AI. Prepare and prime your business for it; invest in R&D, partner with the right AI experts; get buy-in from all stakeholders; train your workforce on generative AI (to use it like intelligent, responsible beings!) and develop policies and procedures that address data privacy, bias and security. It’s also critical to start small by piloting generative AI in a small, focused business area and figuring out what works and what to iterate. Leaders need to stay open to feedback and adjust plans and strategies. Experiment until they find the right approach for their business – and be prepared to pivot sooner rather than later.

Smarter, but certainly not wiser: While there is no denying that generative AI is taking technology into realms once thought to be reserved for humans, the technology has multiple issues that need to be ironed out, before it can be used with full confidence. Factual inaccuracy is one. ChatGPT, Bard and other content-centric tools often generate results which sound plausible but are completely or significantly inaccurate. The content is often excessively verbose and repetitive. The user also needs to use prompts (input questions) that are specific, clear and simple, to generate the optimal output.

A more serious issue is bias, stereotyping, and discrimination in results, which pose a significant challenge to AI’s responsible development and use. When I asked Dall-E 2 to generate a picture of a four-member Pakistani team working on a tech project, it sadly showed not a single woman in the four picture options it created. Similarly, a request to create the image of a 36-year-old Pakistani woman resulted in all the four women wearing a hijab. The algorithms simply reinforced the false generalisation that women in Pakistan do not work in tech fields, or that all Pakistanis are Muslims and cover their heads. This type of biased AI perpetuates stereotypes and discrimination, leading to negative outcomes for individuals and society, further contributing to the marginalisation of certain groups.

Embrace, not fear, the tech: Now for the inevitable question that shadows every AI-related discussion. Will generative AI affect jobs? Absolutely yes! A recent report by Goldman Sachs estimates that around 300 million jobs could be affected by generative AI, meaning 18% of work globally could be automated, with advanced economies more heavily impacted than emerging markets. Just as previous generations witnessed sweeping changes in the aftermath of the Industrial Revolution, the adoption of AI technologies will have a similar, if not greater impact. However, remember that AI and generative AI can augment and not replace human expertise. Human ingenuity is unique, complex, contextual and multidimensional. It is not simply a matter of gathering information and generating ideas/content. Human ingenuity is about being able to think outside the box, to be creative, empathetic, unique, and authentic – qualities generative AI tools cannot emulate. Going back to the examples at the beginning: the work anniversary speech might be comprehensive and grammatically correct, but it will not carry the emotion and experience of a person. The generated article will meet the word count and cover the specified outline but is likely to be verbose and devoid of unique style and expression. Then there is the issue of copyright infringement and plagiarism, which warrants a separate article in itself.

Make value for your North Star: As technology transforms how we work, business leaders and individual professionals need to take a strategic tack. Generative AI is not only about automation, it is about augmentation and acceleration. It is about unlocking human potential to do tasks differently, and do different higher-value tasks. For leaders, a progressive approach is to break down certain job/work functions into different tasks, and identify which of them are human-only, which can be automated, augmented, and which are new ‘emergent’ tasks. This is the new mix of tasks around which companies should redesign jobs that truly make value for their North Star.

For individual professionals, it’s crucial that they hone their creative, analytical and ingenious problem-solving skills – traits that make them unique. According to the World Economic Forum, automation and technology will eliminate 85 million jobs – while creating 97 million new ones. So wake up, upskill and reskill for ‘jobs of the future’. Definitely use generative AI tools as your chota (assistant) or sidekick for speedy and tedious research, drafts and creative mocks, but rely on your unique ‘supremely human’ self to bring that final X factor!

Amber Arshad is Manager, Content and Digital,10Pearls.
amber.arshad@10pearls.com