Every decade or so, the tech sphere witnesses innovations that drastically alter how we perceive and interact with technology. The widespread proliferation of the internet transformed global communication, and now, generative AI stands at the cusp of another monumental shift. But, as with all technological advancements, it’s essential to discern between the transformative potential and the surrounding hype. TSIA’s research teams are endeavoring to shed light on this very distinction with our latest “TSIA AI Capabilities Landscape” report.

In this blog, we will outline some of the key findings in this report so that you can find ways your organization can use AI both now and in the future.

Deep Dive into the Landscape of Human Competence

To truly grasp the potential of AI, it’s important to first understand its relationship with human competence. This comparison isn’t new. Hans Peter Moravec, a giant in robotics and AI, tackled this in his influential paper, “The Landscape of Human Competence.” Max Tegmark, a renowned physicist, then took Moravec’s concepts and visualized them, crafting a vivid and easily graspable image.

Picture a serene, expansive landscape where mountains represent different human capabilities and the waterline represents areas that have already been successfully mastered by software. Some of these, like the skill of playing chess or doing math, are already submerged underwater, indicating AI’s mastery over them. On the other hand, specific peaks, symbolizing tasks like writing an intricate novel or proving complex theorems, remain untouched by AI, standing tall and majestic. But, as AI evolves, the rising water levels threaten to engulf more of these peaks.

The TSIA AI Capabilities Landscape: Charting New Waters

Building upon Moravec’s foundational concepts, TSIA’s research team has introduced a modern visualization to monitor AI capabilities within the tech sector. This model divides AI adoption into:

• Below the Waterline: This encompasses AI capabilities that are now a standard in the industry. Most companies have already adopted and implemented these.
• At the Waterline: These are AI features undergoing rigorous testing and fine-tuning. They represent the immediate future of AI deployment.
• Just above the Waterline: These capabilities have piqued companies’ interest. They’re on the horizon and might be piloted in the coming year.
• Well above the Waterline: These are the long-term prospects, the capabilities that forward-thinking companies believe will reshape the landscape in the next three to five years.

Furthermore, TSIA provides granularity by segmenting these capabilities based on varied organizational roles:

• Customer Success (CS)
• Education Services (ES)
• Managed Services (MS)
• Offer Management (OM)
• Professional Services (PS)
• Revenue Management (RM)
• Support Services (SS)
• Field Services (FS)

Such segmentation not only facilitates an in-depth understanding of AI’s multifaceted role, but also assists companies in strategizing AI implementation across diverse business verticals.

The Art Project Syndrome in Corporate AI: A Need for a Shift

Today, an astonishing 90% of companies are treating AI akin to an art project, with every department essentially “painting their own picture.” This fragmented approach sees a lack of formal funding and little to no efforts for cross-functional alignment. But here’s the kicker: to truly thrive, a successful AI strategy (and its execution) necessitates a cohesive digital transformation, fostering an environment that enables the entire business.

It’s important to note that the foundation of AI is data. Yet, the sobering reality is that over 70% of digital transformations have been met with failure. Why? Because, much like our aforementioned “art projects,” these transformations often lacked structure and direction. If companies don’t pivot, the AI enablement failure rates will mirror these staggering statistics.

However, there’s light at the end of the tunnel. TSIA is in the process of developing a fresh framework focusing on the three dimensions of AI. At its core? Data-driven decision-making rooted in data science and analytics.

This key principle not only paves the way for efficiency and cost reduction but also magnifies the customer experience. If businesses seek a roadmap to enhance their AI prowess, prioritizing data-driven decision-making should be step number one. As we embark on this AI journey, let’s shift from scattered canvases to a unified masterpiece.

The Current State and The Road Ahead

As part of its pioneering efforts, TSIA has documented these AI capabilities in the tech industry. However, this blog offers a mere snapshot. With the tech world’s dynamic nature, TSIA’s research remains ongoing, continually unearthing insights on how various organizations leverage AI, its challenges, and its undeniable advantages.