The Hype Curve of AI and Edge Computing: Why Investment in Mid-Market ISVs and SIs is Crucial for Building Trust and Scaling Adoption

In today’s rapidly evolving technological landscape, artificial intelligence (AI) and edge computing are at the forefront of innovation. Both technologies promise to revolutionise industries from manufacturing to healthcare by enabling faster data processing and decision-making at the source. However, like many disruptive technologies, AI and edge computing are following a familiar path — the Gartner Hype Cycle — where initial excitement must give way to practicality, trust, and eventually, widespread adoption.

But how do we ensure that AI and edge computing transition from hype to trusted, scalable solutions? A key factor lies in enabling and investing in mid-market Independent Software Vendors (ISVs) and Systems Integrators (SIs). These players, though often overlooked compared to Global System Integrators (GSIs), are vital in the early stages of delivering AI and edge computing solutions to market. In this article, we’ll explore why mid-market ISVs and SIs are crucial for scaling AI and edge computing, while reflecting on lessons learned from previous technology adoptions where hardware integration needs slowed the adoption cycle among GSIs.

The Hype Curve: Where Are We Now?

At this point, AI and edge computing are riding high on the hype curve. Enterprises and organisations are investing in proof-of-concept (PoC) projects, eager to demonstrate how these technologies can deliver business value through increased automation, real-time analytics, and enhanced security at the edge. However, as excitement peaks, the industry will soon move into the “Trough of Disillusionment,” where the challenges of scaling become evident without the right trust infrastructure and proven success stories.

Why Mid-Market ISVs and SIs are Key to Early-Stage Growth

Mid-market ISVs and SIs have historically played a pivotal role in turning emerging technologies from promising prototypes into viable, scalable solutions. When it comes to AI and edge computing, their ability to innovate quickly and adapt to customer needs enables them to play a crucial role in overcoming the challenges that arise in the early stages of adoption.

1. Agility in Solution Delivery: Unlike larger GSIs, which tend to focus on massive enterprise-level projects and long-term contracts, mid-market ISVs and SIs are more agile. Their size allows them to respond swiftly to market demands, customise solutions more efficiently, and provide hands-on customer support. This agility is essential when navigating the early stages of AI and edge computing, where smaller, tailored solutions often lead the way.

2. Niche Expertise: Many mid-market ISVs focus on niche applications of AI and edge computing, such as predictive maintenance, security monitoring, or real-time data analytics in specific sectors. These targeted solutions provide immediate value to customers, helping to build trust in the technology by delivering tangible results. Once trust is established, broader adoption becomes more feasible.

3. Faster Time to Market: Mid-market SIs are often able to integrate new hardware and software solutions more rapidly than their larger counterparts. This is crucial for AI and edge computing, which frequently require integration with specific devices, sensors, and on-premise systems. The ability to deploy quickly helps overcome the initial inertia of scaling new technologies.

Learning from the Past: Why GSIs Are Slower to Scale in Early Stages

Looking at previous technology waves, such as cloud computing and IoT, a familiar pattern emerges: GSIs are often slower to scale new technologies in their early stages, particularly when hardware integration is required. This is not due to a lack of capability, but rather the scale at which GSIs operate. Global System Integrators typically focus on multi-year transformation projects with large enterprises. The complexity and bureaucratic processes involved often slow down the integration of new hardware-heavy solutions.

For example, in the early days of cloud adoption, many GSIs focused on massive infrastructure shifts, while mid-market SIs provided more agile solutions, helping companies adopt hybrid cloud strategies. Similarly, in IoT, mid-market players were quicker to deploy hardware-driven solutions at the edge, enabling faster proof of concepts and generating early wins for the industry.

The Role of GSIs as the Market Matures

While mid-market ISVs and SIs are critical in the early stages of AI and edge computing, GSIs will play a key role as the market matures and scales. Once trust in the technology is established, larger enterprises will turn to GSIs for their ability to manage complex global implementations, multi-region deployments, and broader digital transformation initiatives.

As AI and edge computing solutions become more sophisticated and integrated into the broader IT infrastructure, GSIs will be instrumental in delivering end-to-end solutions that encompass cloud, on-premise, and edge environments. In other words, mid-market ISVs and SIs may lead the charge in the early stages, but GSIs will be essential to driving mass adoption as the market evolves.

Building Trust Through Investment

The success of AI and edge computing ultimately depends on building trust in the technology — trust that the solutions are secure, reliable, and scalable. This trust can only be established through investment in enabling mid-market ISVs and SIs. By supporting these smaller, more agile players, enterprises can achieve quicker time to value, create compelling proof of concepts, and lay the groundwork for broader adoption further down the line.

Venture capital, private equity, and corporate investors need to recognise that mid-market ISVs and SIs are not just a stepping stone but a critical component of the AI and edge computing ecosystem. Without them, the journey from hype to mainstream adoption would be significantly longer and more arduous.

Conclusion: The Future of AI and Edge Computing

AI and edge computing are poised to reshape industries and create new opportunities for innovation. However, moving beyond the hype will require strategic investments in mid-market ISVs and SIs, whose agility and niche expertise allow them to deliver early wins and build the trust necessary for larger-scale adoption. While GSIs will be crucial in the long term, scaling these technologies in the early stages depends on the efforts of smaller, more nimble players who can bring AI and edge computing solutions to market quickly and effectively.

The next few years will be critical in determining how far AI and edge computing will scale, and where mid-market ISVs and SIs play a vital role, investors and enterprises alike must recognise their importance in the ecosystem.

By Paul Wealls

AioT Hub