The excitement around Artificial Intelligence (AI) is palpable.
Dec. 5, 2023
From originating in the niche circles of technologists in the 1950s to being accessible nearly everywhere today, AI has transcended boundaries and come a long way, leaving a lasting imprint on the world. With its market size projected to surpass US$407 billion by 2027, AI is undoubtedly a force to be reckoned with.
Many believe that the advent of Generative Artificial Intelligence (Gen AI) marks a watershed moment in the historical evolution of AI, blurring the lines between fiction and reality. In fact, its automation capability, out-of-the-box accessibility, and ability to democratise usage make Gen AI stand out from all other preceding versions of AI technology. From generating real-time suggestions for sales representatives to tailor-make their customer calls to predicting stock trading trends, composing academic essays and writing software code – Gen AI has the potential to be at the front and centre of nearly every industry vertical given its wide-ranging applications, adding upwards of US$4.4 trillion annually to the global economy.
Amidst the plethora of noise surrounding Gen AI, business leaders are rushing to keep pace with its rapid developments and holistically gauge its perks and perils. With tools such as ChatGPT, DALL-E2, and GitHub Copilot galvanising public attention and fuelling a breathless discourse, organisations face the million-dollar question: to Gen AI or not to Gen AI?
Is The Hype Real?
Gen AI is a type of AI technology that “learns” patterns from existing data and utilises this knowledge to generate new content when prompted in the form of audio, video, text, animation, and 3D models. Since the launch of OpenAI’s ChatGPT in November 2022, which instantly became a household name by rocketing to 100 million users in its first two months, Gen AI has been a subject of great intrigue and public scrutiny, polarising opinions across the board.
Proponents believe it is a game changer that will bring a paradigm shift to the industrial landscape and will not just be another also-ran on the list of “the next big thing”. Sceptics are quick to point out that anything that rises so spectacularly is bound to fall the same way, and there is still unchartered territory and plenty of choppy waters to navigate through the ocean of Gen AI. As the age old saying goes – you can love it, you can hate it, but you cannot ignore it. Gen AI is a case in point.
With the potential of disrupting industries like never before, organisations face several burning questions when it comes to deciding whether to implement Gen AI or not. Should we act now? If so, how should we start? How much should we invest? Do we have the right people and infrastructure in place? Can we set guardrails to mitigate the risks? What does the future behold?
These are all pertinent questions that necessitate in-depth assessment. Grasping the potential ramifications of Gen AI and how that impacts day-to-day operations requires a step-by-step approach, so organisations are positioned to leverage the benefits while remaining cognisant of the red flags. Step one is looking beyond the Gen AI hype and evaluating the core facts.
Major Points to Ponder
Finding the right balance between excitement and pragmatism towards Gen AI is key. There is no one-size-fits-all approach, as the viability of adopting Gen AI tools is unique to each organisation’s reality. Thinking beyond immediate gains and focussing on devising long-term plans should be of utmost priority in boardroom discussions.
Consider these key aspects when making decisions on Gen AI implementation:
- Justified Use Case: Gen AI has several use cases that can impact marketing, customer service, product design, analytics, software development, and other functions. However, before implementing it, a specific pain point should be identified, which a Gen AI tool can then alleviate. Businesses should carefully evaluate whether the use case is applicable and within scope, and whether adopting a Gen AI tool can accelerate value creation and the fulfilment of their overall objectives and key results.
- Infrastructure Integration: Implementing Gen AI without having a robust technical infrastructure in your organisation is a recipe for failure. Selecting the right foundation models upfront as well as the supporting natural languages and programming languages are the building blocks for subsequent platform engineering, process transformation, and automation efforts. CTOs need to conduct a thorough assessment of their current technology landscape to identify potential issues in the existing architecture and iron out compatibility issues while integrating the new solution.
- People and Skillset: Involving people with the right know-how, skills, and foresight towards implementing Gen AI is another key piece of the puzzle. It is important to drive cultural buy-in by involving different teams and collectively understanding its benefits and pitfalls through pilot initiatives. If the existing bandwidth is limited, this could necessitate hiring new talent or partnering with subject matter experts to bring the latest research and insights to the table.
- Return on Investment: Implementing transformative Gen AI use cases comes with significant financial implications and risks. Due diligence and in-depth cost-benefit analysis must be conducted to investigate if the intended results can be achieved from the investment. The upfront costs to adopt the use cases are typically high, so companies need to have a sufficient safety net to get through the initial phase where direct returns might be scarce.
- Trust and Safety Mechanisms: There are a multitude of concerns pertaining to ethics, security, and misuse of Gen AI tools. Given the potential misinformation and biases that are fed into the AI models, it becomes critical that the right processes and guardrails are set in motion to address data quality and privacy concerns. Ethical implementation of Gen AI should be a non-negotiable, with senior management setting the tone.
The Road Ahead
Given the ever-increasing complexity of Gen AI, the learning curve for businesses is steep and unrelenting. While there might be a fear of lagging behind competition, it is important that C-level executives don’t get carried away by the popular narrative and act impulsively, but rather temper expectations, plan strategically, and drive informed decision-making. Embracing change as the only constant, they need to think unconventionally, lead with conviction, and be bold to challenge the status quo. With the right mix of technical infrastructure, talent and skills, investment, and risk management, organisations will be better equipped to cope with developments in the field of Gen AI, thereby becoming future-ready.
In the years to come, the automation capabilities, intelligence, speed, and scale of these tools are expected to magnify in leaps and bounds, thereby necessitating greater accountability, responsible implementation, and proper governance. It is time for organisations to bring their A-game to the forefront by keeping up with changing trends, unlocking opportunities from challenges, and seizing the business imperative.