The world of artificial intelligence continues its profound transformation and accelerating maturity. Numerous advanced AI language and machine learning models are on the verge of commercial availability. These models, developed by leading organizations and research institutions, are set to redefine the boundaries of what AI can accomplish. Let’s take a glimpse into the near future and explore the transformative potential of these technologies.
Driven by breakthroughs in deep learning, natural language processing, and advanced algorithms, these advanced AI models promise to revolutionize industries in multiple ways. By leveraging vast amounts of data, Natural Language Processing (MLP) and Large Language Models (LLM) are being trained to understand, and generate, human-like language, paving the way for more engaging, interactive, and personalized experiences. They will far surpass the leading-edge models available currently, such as Jasper.ai.
We expect the next commercial offerings to continue to have their own limitations, but as they continue to progress, these AI models will exhibit a range of remarkable capabilities, including enhanced language comprehension, context-awareness, and problem-solving skills. They can engage in dynamic conversations, provide detailed explanations, offer intelligent recommendations, and even display creativity. These advancements open up new possibilities in areas such as virtual assistants, customer support chatbots, content generation, and more.
We predict that the maturation of AI will follow a similar path to that of software generally. The desire for organizations to develop their own AI models will still exist, at least for the next few years, particularly in machine learning which connect dots within unique “big data” datasets. But as time progresses, we expect the large software firms to develop and enhance commercial libraries and services to the point where “basic AI” capabilities can be subscribed or licensed, rather than requiring development. Just as enormous swaths of IT employment has shifted from developing custom software to customizing Platform as a Service (PaaS) systems, we predict that data scientists in most companies will make a similar shift in their day-to-day responsibilities. And of course, this transition further swings open the door to “citizen data scientists” by packaging and modularizing key capabilities needed for AI.
As a result of the upcoming commercialization, ethical considerations and responsible AI practices will continue to increase in importance and scrutiny. The leading organizations investing in these advanced AI models are keenly aware of the importance of bias mitigation (particularly in training dataset selection), privacy protection, and transparent decision-making.
The potential applications of advanced AI language and machine learning models are virtually limitless. In healthcare, these models can assist in diagnosing diseases, analyzing medical records, and offering personalized treatment recommendations. In financial services, they can aid in fraud detection, risk assessment, and portfolio management. The possibilities extend to real estate (residential & commercial), energy, retail, manufacturing, aerospace, business services, logistics, education, food service, entertainment, tourism, legal services, insurance, and beyond.
As these advanced AI models approach commercial suitability, businesses and industries should escalate their efforts to embrace AI. Adopting and integrating AI models into existing and streamlined workflows will require strategic planning, skill development, and an openness to innovation. Organizations that leverage these AI technologies will gain a competitive advantage, driving efficiency, enhancing customer experiences, and unlocking new avenues for growth and innovation.
It will be critical for business leaders to leverage outside expertise to navigate this leading-edge landscape, to know where the advancing line of viability is at any point of time, and to know which processes and functions are inside it and outside it.
As exciting as the next few years will be, and while these AI models will demonstrate exceptional capabilities, they will not be without limitations. It will be critical for business leaders to leverage outside expertise to navigate this leading-edge landscape, to know where the advancing line of viability is at any point of time, and to know which processes and functions are inside it and outside it.
A new era of artificial intelligence (and really, of IT automation generally) is right around the corner. By beginning the ideation and prioritization processes now, organizations can ensure they are ready, not just to adopt these technologies, but to truly leverage them for competitive advantage, when they become viable.
