2024 marks an exciting chapter in our ongoing TSIA Research Journey on Artificial Intelligence (AI). It’s a year that unveils a remarkable eagerness among companies to embrace the boundless potential of AI and harness its myriad benefits. It’s perfectly understandable: AI’s allure is undeniable, promising increased efficiency, enhanced decision-making, and a competitive edge like never before.

However, amidst this enthusiasm, a gap has emerged that can’t be ignored. As we delve into the heart of this year’s research, we’ll spotlight a critical issue that plagues many organizations: the absence of robust governance and the urgent need for a formalized process for adopting and harnessing AI.

In this blog, we’ll explore how companies can navigate the dynamic world of AI, establish solid governance frameworks, and embark on a path toward unlocking the full potential of this transformative technology.

Bridging the Governance Gap in the Age of AI

The 2023 TSIA Envision conference illuminated a critical theme that demands immediate attention: the need for organizations to strategically merge technology and human expertise. This fusion, fueled by AI, promises to enhance productivity and redefine the essence of how businesses operate.

Yet, despite the potential of AI, a surprising number of companies still stand on the threshold, hesitant to fully embrace this technology. The question that arises now is why?

Our research reveals a widespread deficiency in how companies structure their AI initiatives. Despite substantial investments in AI, the absence of formalized processes and a lack of company-wide ownership of AI initiatives paint a sobering picture. It’s a scenario that underscores the failure of many organizations to truly grasp the magnitude of AI’s impact.

Moreover, our findings identify a glaring absence at the C-level: a designated leader to oversee AI strategy. This leadership void raises questions about the coherence and direction of AI endeavors within these organizations, a concern amplified by the stark lack of documented AI implementation success among most respondents to our 2023 Organizing for AI Success quick poll.

Navigating the path to translate AI investments into tangible success metrics is undoubtedly challenging. However, hope is on the horizon: our research indicates that certain practices yield promising results. Companies that boast a C-level executive tasked with AI strategy or a centralized data science organization tend to outperform their peers. It’s a clear indicator that having a strategic approach pays dividends in the world of AI.

Conversely, it’s no surprise that companies without allocated funds for AI development find it more challenging to document AI success. Financial commitment is pivotal in the intricate dance between investment and outcomes.

As we venture further into the AI landscape of 2023, the message is clear: bridging the governance gap is essential. It’s a journey that will demand adaptability, strategic thinking, and a commitment to innovation.

Navigating the AI Landscape: Diverse Adoption Trends Among Organizations

When it comes to AI, one size does not fit all. Organizations are charting diverse courses on their AI adoption journeys, and while the promise of AI-enhancing service delivery is universally acknowledged, the extent to which it has been embraced varies significantly.

Consider the landscape among managed services organizations, a sector ripe for AI’s potential. Surprisingly, many are still on the cusp of unleashing AI’s power. In a quick poll conducted in 2023, a striking 63% of respondents revealed that AI capabilities remained largely untapped within their organizations.

When probed further about specific technologies they aspire to implement, the results offered some interesting insights—over a quarter expressed keen interest in robotic process automation (RPA), while just under 20% showed enthusiasm for generative AI, natural language processing (NLP), and data analytics. A smaller, yet significant, group (around 10%) aimed to integrate AI-related data science capabilities.

This diversity in interests and priorities underscores the nature of AI adoption. It's a landscape where organizations customize their AI journey to align with their unique needs and goals.

Shifting our focus to revenue generation, another crucial facet of AI’s impact, the 2023 AI and Revenue Growth and Retention quick poll paints a revealing picture. For many companies, AI’s role in revenue generation is still in its infancy. Nearly half are in the information-gathering phase, seeking to understand AI’s potential; 39% are actively testing specific AI applications or technologies to assess their feasibility and impact.

Yet there are still signs of hesitation. The results suggest that many companies have not yet adopted deliberate, long-term strategies to harness AI’s full potential for revenue generation. Alarmingly, nearly half have not allocated a specific budget for revenue-generating AI initiatives, hinting at a potential disconnect between aspiration and action. Moreover, a substantial 37% are still defining or assigning ownership for AI development, revealing potential gaps in accountabilities and responsibilities within AI initiatives.

Each organization’s journey to AI excellence is unique and shaped by its vision, priorities, and readiness.

Navigating the AI Maze: Challenges on the Road to Implementation

As organizations work to harness the potential of AI, they encounter a landscape dotted with challenges, hurdles, and opportunities. In exploring AI capabilities in managed services, we’ve unearthed valuable insights into the obstacles to seamless implementation.

At the forefront of these challenges is the quest for skilled AI talent. Unsurprisingly, this hurdle looms large, as AI’s complexity demands expertise, often in high demand but short supply. According to our findings, the lack of skilled AI talent emerged as the most significant challenge organizations face. It’s a roadblock that can deter even the most enthusiastic AI adopters.

Closely trailing behind is the concern about integrating AI into existing systems and workflows. The intricate dance of merging cutting-edge technology with established processes is delicate. As organizations strive to embrace AI, this challenge takes center stage, emphasizing the need for careful planning and strategic alignment.

But it’s not just skills and integration; the investment issue also looms large. Our research underscores the importance of governance, as insufficient investment remains a key stumbling block. Investment decisions are not just financial; they reflect an organization’s commitment to its AI journey.

In the world of AI, knowledge is power. However, our findings highlight another critical challenge: the absence of a process for sharing lessons learned from AI deployments across departments. Over 70% of respondents reported this hurdle. The facts are clear: Keeping AI knowledge siloed, especially in the early stages of adoption, can hinder progress and stifle innovation.

The path to AI success is not a solitary one; it’s a collective endeavor. Organizations open to sharing knowledge and experiences are likely to accelerate the development of AI solutions that benefit the entire company. It’s a reminder that collaboration and knowledge-sharing are vital components of AI implementation.

Unleashing the Power of AI: The Crucial Role of Data in Strategy

In the world of AI, the stage is set for a journey that promises to redefine service delivery and customer support. The rise of chatbots and generative AI in support services is a testament to AI’s potential to reshape our interactions with technology.

However, amidst the excitement of AI’s capabilities, a fundamental truth cannot be ignored: Data is the lifeblood that fuels the AI engine. Without it, the application of AI or machine learning remains limited in its scalability and repeatability. A robust data strategy must take center stage to chart a course for success in AI.

At TSIA, we advocate for a holistic approach to AI implementation. We firmly believe that a corporate-wide data science and analytics function is beneficial and essential. It forms the bedrock upon which successful AI initiatives are built.

The 2023 The Role of Data in Predictive and Proactive Support quick poll reaffirmed data’s pivotal role in AI. While most companies possess some level of data capabilities, there’s a significant gap waiting to be bridged when fully leveraging product and software telemetry and prescriptive analytics.

Regarding telemetry, it’s evident that most companies have a substantial journey ahead. Descriptive data utilization represents the first step, providing valuable insights into past events. However, the real potential lies in predictive data use cases, such as preventative maintenance, which promise to revolutionize organizations' operations. A significant proportion (26%) reported having no predictive data use cases at all, highlighting a considerable opportunity for growth.

Embracing AI’s Promise: Charting a Path to Transformation

As we venture into 2024’s AI landscape, one thing becomes abundantly clear: The desire to harness AI’s immense potential is universal. It’s a desire fueled by significant investments, lofty aspirations, and a genuine hunger for transformation.

However, beneath the surface of this enthusiasm, critical gaps emerge in governance, strategy, and the skillsets that can make or break AI endeavors. The absence of formal processes, the dearth of company-wide ownership, and the lack of dedicated leadership for AI strategy pose formidable challenges.

Yet, these challenges are not insurmountable. They are the crucible in which true innovation is forged. They compel organizations to rethink their approach, bridge the gaps that hinder success, and redefine what's possible.

Our journey through the AI landscape has also unveiled disparities in AI utilization across different sectors. It’s a stark reminder of the need for a cohesive and deliberate approach to AI adoption. It’s a call to action, encouraging organizations to come together, share knowledge, and collectively embrace the transformative power of AI.

The path to AI-driven success is paved with challenges, but also illuminated by immense promise. Bridging the gaps, fostering knowledge sharing, and prioritizing a robust data strategy will be pivotal in realizing the full potential of AI. It’s a journey that promises sustained success and innovation, not just for individual organizations but for entire industries.