Published on October 18, 2023, 4:29 pm
The human-machine relationship is undergoing a dynamic evolution, and one area that is driving this transformation is Generative AI. This technology has the potential to completely revolutionize enterprise processes, decision-making, and strategy in ways we have yet to fully comprehend. It’s no longer just an IT initiative but should be embraced as an enterprise-wide initiative.
At the recent IT Symposium/Xpo, Gartner analysts provided guidance on the significance of generative AI, along with other notable statistics and predictions. In her opening keynote, Mary Mesaglio, distinguished VP analyst at Gartner, described generative AI as more than just a technological trend; it represents a profound shift in how humans and machines interact. We are moving from what machines can do for us to what they can be for us.
Enterprises are starting to recognize the importance of embracing AI. According to a Gartner poll of CIOs, 73% said their organizations plan to increase funding for AI/Machine Learning (ML) by 2024. Additionally, 80% stated that they are planning on full gen AI adoption within the next three years. It’s clear that businesses are strategizing and preparing to embrace this technology. The combination of pretrained models, cloud computing, and open-source platforms will democratize gen AI by 2024.
Gartner predicts that by 2025, generative AI will become a workforce partner for 90% of organizations worldwide. This shift will give rise to new challenges such as AI Trust, Risk and Security Management (TRiSM). These challenges include ensuring proactive data protection, monitoring for data and model drift, securing inputs and outputs of AI systems, and implementing risk controls.
Another intriguing prediction from Gartner involves “custobots,” machine customers that autonomously negotiate and purchase goods and services. By 2028, it is projected that there will be approximately 15 billion connected products behaving as customers. This development has the potential to disrupt business models and have a significant impact on sales, marketing, and human resources.
As we prepare for the future of AI, it’s essential to understand two categories: everyday AI and game-changing AI. Everyday AI serves as a productivity partner, enabling workers to accomplish their tasks more efficiently. However, with time, everyday AI will become commonplace, leveling the playing field among competitors. On the other hand, game-changing AI acts as a creativity partner by generating new results, products, and services that disrupt industries.
To make the most of AI adoption, enterprises must examine opportunities and risks in various areas such as back-office processes, front-office interactions, new product development, and core capabilities. It’s crucial for C-suite members to establish “lighthouse principles” aligned with organizational values that guide AI implementation. Making data secure, fair, accurate, enriched, and governed by these principles is also critical.
Enterprises should be prepared for new attack vectors by implementing AI-ready security measures while establishing acceptable use policies. It’s important to note that generative AI is not the only technological advancement businesses need to consider. There are numerous technologies connected to it that enterprises should explore in order to understand how they interact with machines and what they can achieve.
When adopting new technologies like AI or undergoing digital transformation initiatives in general, it’s vital for organizations to shift their focus from solely pursuing productivity gains or short-term outcomes. It’s necessary to have meaningful conversations about how humans want to interact with machines and intentionally shape those relationships. By asking the right questions and investing in prompt engineering skills within existing teams rather than relying on new hires alone can ensure successful integration of gen AI into enterprise operations.
As we move forward into an era where machines play increasingly significant roles in society and business contexts alike, it becomes crucial to strike a balance between humanizing them through interfaces while avoiding going too far in anthropomorphization. Cultivating direct interaction between humans and machines while ensuring technological and ethical boundaries are respected is key to unlocking the immense potential of generative AI.
The future looks promising for AI, and businesses must embrace this wave of innovation. By aligning AI initiatives with organizational values, investing in upskilling existing experts, and effectively questioning technology, enterprises can harness the power of generative AI to drive growth, disruption, and meaningful results.