We are at the very beginning of the next industrial revolution. Technology is reshaping the way we work, unlocking new levels of efficiency, productivity and innovation. Generative AI has emerged as that very technology and is having a significant impact on almost every sector. It’s a ground-breaking force, promising to revolutionize the way we create, generate and manage content. It’s pushing the boundaries of what was once thought possible. To understand how it can create a competitive edge, it’s crucial to get to grips with generative AI’s inner workings and the questions it raises.

    What is generative AI? 

    To fully grasp the significance of generative AI, it’s essential to understand how it differs from other AIs. Put simply, it’s a branch of the technology that creates new content that’s inspired by, or similar to, what’s gone before.

    While traditional AI is often based on classification or prediction tasks, generative AI goes beyond that. It produces things by learning patterns and structures from the data it’s trained on. This presents a world of creative possibilities, allowing AI models to generate text, images and even music that didn’t exist before. Think of it as having an AI-powered artist or writer at your disposal.

    “Generative AI is poised to drive the next industrial revolution, leading to signification shifts in the world of work. Unlike previous revolutions that took months or years, this transformation is happening at break-neck speed.”

    Data is the key

    Unlike Large Language Models (LLMs) that require large datasets to function, other generative models can often operate on a smaller scale. For example, models like Generative Adversarial Networks, commonly used for image generation or data augmentation, can still operate just as efficiently on relatively small datasets. Of course, generative AI models do benefit from larger datasets, as the more diverse and higher quality the data is, the better the model can understand the patterns that’ll influence the output quality.

    The reliance on datasets is essential as these models aim to capture the nuances, intricacies and patterns of the data they learn from, setting generative AI apart and making it a powerful tool for innovation and creativity.

    However, while these models excel at generating content, they’re still reliant on the data they were trained on. They lack real-time awareness and may not be up-to-date with events or information that occurred after their training data was collected. Yet, the power and possibilities that this branch of AI holds are both exciting and transformative.

    “Organizations will need to integrate generative AI into the automation of an end-to-end process. Once enterprise-ready, the future of work will witness remarkable changes and face many questions.”

    How will it change the future of work?

    Generative AI is poised to drive the next industrial revolution, leading to significant shifts in the world of work. Unlike previous revolutions that took months or years, this transformation is happening at break-neck speed. It’s taking place so fast that tech leaders have called for a pause in its development and governments are grappling with its regulation.

    It’s going to take on more and more tasks that people currently do. From administration and customer service to coding and architecture, roles that once relied on uniquely human skills will increasingly be given to generative AI.

    As it does so, organizations will need to leverage intelligent automation solutions that integrate generative AI into the automation of an end-to-end process, rather than for specific tasks or productivity enhancements. Once enterprise-ready, the future of work will witness remarkable changes and face many questions. These include:

    1) A blurred line between humans and bots

    Generative AI will see activities like content production fully automated, accelerating the adoption of straight-through processing for common business processes. Other areas, such as self-service communication channels will also become more prevalent, as generative AI-powered systems achieve a level of competence that’ll blur the distinction between human and bot-driven communications.

    2) Enhanced employee productivity

    As the technology becomes more readily available, organizations will see it adopted and built into the day-to-day applications and tools that employees use, such as Microsoft Office, as a way to enhance employee productivity and complete mundane and time-consuming tasks for them. At an individual level, knowledge workers will need to familiarize themselves with how to leverage the technology to work smarter and faster than before.

    However, for businesses to fully harness the potential of generative AI, business leaders must understand how to effectively integrate these technologies more widely into their existing workflows to fuel efficiency and drive innovation. Without doing so could lead to a competitive disadvantage.

    3) Bypass the AI hallucination trap

    With generative AI taking on simple creative tasks, there will be new opportunities for businesses specializing in higher-value endeavors, such as strategy, planning and high-end creative content creation. Now that everyone has access to AI, the key to staying ahead of the competition lies in crafting content that surpasses the capabilities of the AI systems.

    It can even present opportunities in the future for other services to emerge that will assess, correct and challenge content that’s created by generative AI systems. These future endeavors can help to authenticate whether content is AI-generated or human-generated, ensuring quality assurance and better supporting organizations from falling into the “AI hallucination” trap.

    4) Leveraging open source models

    Enterprises will need to work out if they should use open source models, like ChatGPT or MidJourney, or create their own generative AIs. Using existing software might present security or data protection issues, yet going it alone could be wildly expensive and take time. There’s a lot to consider, meaning SMEs and mid-market companies are likely to integrate what’s readily available, but doing so will also mean implementing effective safety and control measures.

    “Generative AI will transform financial services. For example, fraud detection through pattern recognition and generate synthetic data for risk assessment algorithm development”

    How to use generative AI now? 

    Generally speaking, the technology can be used to support two scenarios:

    • Actionable insight – answering questions or offering insight based on a query or data set
    • Actionable content – creating a specific piece of content that can be used and/or adapted.
      While it’s tempting to ask, “What can it do?”, this might be the wrong question to ask. The technical functionality and capabilities of generative AI continue to evolve beyond the traditional question-and-response approach.

    A more useful and enjoyable approach to knowing how to use generative AI is to first experiment with different prompts and witness the model’s performance in various scenarios. Hands-on experience not only helps in understanding the technology but also further fuels creative thinking.

    AI in the world of finance

    After all, generative AI has already been employed in various ways in an array of industries, crafting a novel way in how we complete tasks; from image creation and text completion to generating training scenarios and data analysis. For example, in finance, generative AI can aid fraud detection through pattern recognition, generate synthetic data for risk assessment algorithm development and provide financial planning and advisory assistance where possible.

    Improving customer relations

    In customer services, conversational agents engage in natural language conversations with users to understand queries and generate appropriate responses. These virtual assistants or chatbots better facilitate personalization, recommend the next best actions or responses, and ultimately, create more engaging and relevant user experiences.

    “While generative AI offers practical and powerful solutions to various challenges, it may also lack knowledge and experience past a certain timeframe. For now, human intervention will be vital.”

    It’s not the “how” but the “why”

    Once you’ve got to grips with how generative AI can be used. It’s then a matter of thinking about why you should use it. What do you want to achieve, how can it be incorporated into a deliberate program and how will you measure whether it’s been a success?

    It’s then possible to set it to work as part of an intelligent automation strategy. Perhaps you already have an existing workflow that creates complex reports, which can be hard to digest. Generative AI could solve that problem by creating a summary, bringing out the key elements and providing a narrative. Or if that report needs to be sent to different countries, perhaps generative AI could translate it.

    If a business is suffering from poor productivity, generative AI could have a more general role, offering useful templates and advice so workers no longer have to start from a blank sheet of paper. By kicking off a task or taking it as far as possible, workers will be more able to complete them, using their human ingenuity to do the rest. This could undoubtedly save effort and money across a business.

    However, it must be remembered that whilst this new and exciting software offers practical and powerful solutions to various challenges, it may also lack knowledge and experience past a certain timeframe. For now, human intervention will be vital.

    Time to delve deeper into generative ai?

    To truly harness the power of generative AI, it’s essential to have a connected and enterprise-wide AI strategy and delivery roadmap. Simply playing around with this powerful new technology or sporadically using it in tactical instances may actually hold it back in the long term.

    At Tquila Automation, we design and deliver AI-powered automation solutions tailored to meet our client’s needs and desired outcomes. We create scalable and flexible solutions that adapt to evolving user demands. Beyond implementation, our dedicated team provides ongoing maintenance and support for any technical issues you may encounter, ensuring more bang for your buck.

    Talk to one of our experts, stop by our booth at UiPath FORWARD or schedule a meeting.