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The Predictable Cycle of Tech Adoption and Navigating Generative AI’s Path to Maturity

Learn more about where generative AI is in the adoption hype cycle, and how organizations can take a pragmatic approach to its adoption and implementation.

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In the ever-changing landscape of new tech advancements, we see familiar patterns emerge in relation to organizational adoption. Gartner’s Hype Cycle accurately reflects the consistent manner by which new technologies are embraced: first excitement, then disillusionment, and ultimately understanding. Generative AI is no exception. This blog explores where generative AI is in the hype cycle today, what it means, and how organizations can take a pragmatic approach to its adoption and implementation.

The Evolution of the Generative AI Adoption Cycle

Kickstarted by the public launch and meteoric user growth of Open AI’s GPT-3.5 in November of 2022, the sentiment over the last 18 months has centered on the incredible possibilities enabled by generative AI. This hype is the driving force behind the 12K+ applications available now that leverage this groundbreaking technology. And the excitement has been justified, as the productivity benefits of this technology are real and measurable

While optimism remains, signs are emerging that the hype cycle surrounding generative AI is heading towards the “Trough of Disillusionment.” As barriers to adoption and growing pains in the technology persist, we are entering the phase wherein initial, sometimes unrealistic expectations are giving way to the practical implications associated with integrating generative AI securely and effectively. 

It is important to note this shift is not a harbinger of doom for generative AI; rather it’s an indicator that the market is evolving just as it should. This phenomenon was witnessed before with cloud technology and its heralding of digital transformation. This transition is a natural part of the process, and shows that generative AI is maturing. And with maturity comes stability and practical applicability. Organizations that understand and embrace this predictable cycle are well-positioned to capitalize on the value derived from generative AI - both today and in the future.

A Pragmatic Approach to Getting Started With Gen AI 

Drawing from the playbooks honed during previous technology waves, organizations are finding success in leveraging generative AI via a stepped, measured approach that enables both near-term productivity and efficiency gains, while also creating the foundation to layer on additional benefit as solutions mature. Here’s what that journey looks like:

Start Simple

The first step on an effective generative AI journey begins with the basics: provide all employees safe access to versatile, general-purpose models like GTP-4, Claude 3, or Gemini 1.5. The most effective way to do this is through a secure chat interface like Liminal Spaces which allows for discrete data management policies tailored to each team, user, or model instance. 

There is an appetite in some organizations to forego this step out of the gate in pursuit of more complex, all-encompassing projects. But the benefits of providing employees secure access to general-purpose tools as a starting point cannot be overstated. A joint study by Harvard Business School and Boston Consulting Group found that users with access to a simple direct chat experience completed 12.2% more tasks, 25.1% faster, and at a 40% higher quality. 

Employees know these tools are valuable, and are already using generative AI regardless of organizational policy. By starting with the enablement of secure direct access, enterprises can minimize Shadow AI, confidently protect sensitive data, and glean insights into the highest value use cases - while at the same time helping their employees be more efficient and productive in their everyday work. 

Embrace Change Management

After providing secure access to general purpose tools, the next step is to facilitate an adoption and insight-gathering strategy. Dedicate time to educate teams on the intricacies of generative AI and how to use it effectively. Examine user behavior and communicate openly with different groups to understand their experiences. 

By encouraging and analyzing usage, organizations can pinpoint exactly how generative AI is driving productivity, and can help both refine how users engage with these tools, and also identify and proliferate high impact use cases across the entire organization. This collaborative feedback provides key insights that can be used to shape a more comprehensive generative AI rollout strategy as adoption matures.

Build on the Momentum

With a firm foundation and a deeper understanding of generative AI's impact, organizations are now positioned to explore the myriad off-the-shelf solutions that align to their overall AI strategy. Informed by actual usage and data surrounding the most effective deployments, companies can intelligently assess and select the appropriate generative AI-enabled tools that support their adoption roadmap.

Capitalize on the Opportunity

As organizations integrate general-purpose models into daily workflows and deploy AI-enabled applications that maximize productivity, exploration on the complex but really exciting use cases can begin. With a well-informed roadmap, an AI-savvy workforce, and material data on its impact, enterprises can confidently pursue the apex use cases for generative AI that will transform how they do business.

Data Security is Foundational

While the roadmap for adopting generative AI illuminates a path of immense potential, it is crucial to acknowledge that the bedrock of this entire journey is data security. The data privacy and security challenges inherent with generative AI are well documented, and as these tools become more integrated into core business processes, it is imperative that sensitive information remains protected. Inappropriate sharing or misuse of company, customer, or employee data can erode trust, diminish the value of an organization, and lead to significant regulatory and legal repercussions.

Liminal is here every step of the way to help enterprises embrace generative AI while ensuring critical data is safeguarded. From getting started with general purpose models, to leveraging off-the-shelf applications with AI capabilities, to developing and deploying generative AI-enabled applications built in house, the Liminal Platform is designed to help organizations keep sensitive data secure throughout their entire generative AI journey. And with granular security and access management controls, and real-time alerting and logging, Liminal provides organizations with total generative AI oversight, administration, and observability.

Now is the Time to Start

The journey of embracing generative AI is not a destination but a continuous process. As organizations navigate the predictable cycle of tech adoption, it is clear that the time to get started is now. The value is apparent, and the tools and guidance are accessible. By taking a pragmatic, step-by-step approach, businesses can begin to harness the transformative potential of generative AI today. The path to maturity for this technology is paved with important insights, increased efficiency, and the promise of even greater productivity. The sooner the journey is started, the sooner these benefits can be realized.

Click here to talk to the Liminal team about starting your journey today.