DECEMBER - JANUARY9 beginning, guardrails and ethical guidelines did not exist. This led to a bombardment of poor content, services, and the darker side of internet evolution: Dark web and malware. For me personally, the biggest hesitation to the broad adoption of LLMs and AI practices is the high-risk exposure that an ungoverned AI poses to an organisation's proprietary equity. SMBs may be more willing to take risks, but larger organisations will undertake comprehensive checks and balances before they hand over the keys to the kingdom. The Future of Labour in the Workforce and AI as an Enabler, Not a ReplacementIt stands to reason that AI was created to simplify and minimise certain tasks that were ill-suited to human beings to begin with. Complex calculations that would take a machine milliseconds could take a human the equivalent of multiple lifetimes. In this way, AI is doing exactly what it is intended to be: an agent of change, allowing for deployments to be done faster. In summation, AI has a multitude of roles in the future workplace. Some industries will become risk-averse early adopters and, move quickly and ignore the weight of data governance. However, in a great many industries, only once the risk mitigation and relentless testing have been done, AI has the potential to be an enabler, allowing for greater workforce utilisation on work that matters. I can see how these models now put access to what were previously data science team-led capabilities like marketing mix models directly into my hands, reducing reliance on external consultancies. Changing of the Guard: Prompts Replace Coding, Which Makes Data AccessiblePreviously, knowledge of SQL, Python and other programming languages was critical to extracting insights out of large data sets, especially your cloud-based environments and clean rooms. The evolution of AI has changed this with prompt-based engineering. This means that even junior analysts can now extract data without programming language capability, and more than coding, prompting is the new skill set to have. This fundamental change opens up data extraction and insights procurement to a whole new generation of data scientists without requiring the mandatory technical skillsets of yesteryear. Not All Labour Is the SameNot all industries will be impacted equally, but in some cases, AI can replace the menial tasks that junior analysts used to do. This includes basic copywriting, data summarisation, presentation development, customer aftercare services and much more. Now, does this mean that human resources is no longer required? The answer depends on the core mentality of the organisation employing it and the customers at the heart of their operations. You see, human beings are not a fully rational species, and as such, an AI platform built on reason and logic cannot fully address the cognitive imbalances in human responses. Jobs such as business strategists that walk the line between logic and instinct will not be replaced in the short term, but repetitive tasks that distract resources, such as scheduling and data aggregation, can be. All Great Technological Advancements Carry RiskWhile AI has multiple use cases, it still mirrors the birth of many impressive technological evolutions like the internet, where, at the THE OPEN-SOURCE NATURE OF LLMS HAS ENHANCED FUNDAMENTAL CAPABILITY WITHIN MULTIPLE INDUSTRIES AND HAS EVENED OUT THE PLAYING FIELD, WHERE EVEN NEW START-UPS AND SMBS CAN COMPETE WITH ESTABLISHED BEHEMOTHS
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