An AI Take on an Old Debate: Does AI Impact the “End-to-end” vs “Best in Class” Decision?

While the event tech landscape is constantly evolving, some debates have been going on for decades. The discussion about whether to invest in a comprehensive solution or string together a series of smaller ad hoc products is one of them. 

While there is a lot of opinionated rhetoric, part of the reason it’s so ongoing is that new developments are constantly changing the calculus. Whether its better integrations, mergers and acquisitions, or the emergence of powerful AI tools and agents, event professionals have a lot to factor in when deciding how to use their budgets.

This article will go through a number of the questions we often encounter to clarify how a solution’s comprehensiveness impacts performance, and what is really at stake when you go “all in” on one provider or choose a more piecemeal approach.

Do Niche Solutions Really Mean Deeper/Better Features?

Sometimes, but not necessarily.

A lot of people think that niche platforms are better able to dive deep into a solution vertical and offer richer, more complex feature sets to solve a specific problem. However, the extent to which they’re able to do that is based on how well resourced they are, and niche solutions are often younger, smaller in scale and operate with smaller teams. They typically have to prioritize those features that add the most value in the same way that larger end-to-end platforms do. Moreover, because these companies often lack broader market appeal, they often have a smaller pool of clients and events from which they get key feedback about their products and services to inform their product roadmap. 

The reality is that a lot of niche “best in class” products end up being designed to serve niche audiences and struggle to pivot outside of their sweet spot.

As a result, the trend is for companies to expand their functionality as they grow in order to be able to address more of their clients’ pain points and, consequently, more of the market. A lot of larger solutions are therefore also better established, better resourced and more powerful. 

Their longer-term experience and broader appeal often enables end-to-end platforms to home in on features that deliver the most value to the people actually using the platform and cut those that nobody really uses. This doesn’t necessarily come at the cost of feature depth or richness. For example, according to Skift Meetings research that ranked 80 event tech providers on feature competitiveness, Stova ranked in the top three (top two in companies that give event organizers exclusive ownership of their own data).

In fact, the inverse can be true – especially now in the age of artificial intelligence (AI). Larger companies with bigger client rosters and a larger pool of events under their belts are better situated to create powerful AI solutions that benefit from bigger data sets. This is how Stova is able to offer effective AI-powered networking and content recommendations that drive a truly personalized attendee experience at scale. 

How Do Mergers and Acquisitions Affect the Logic of “End-to-End”?

A lot of “best in class” proponents rely heavily on clean, simple integrations and providers that “play well with others.” From their perspective, if a provider’s end-to-end solution is just Frankensteined from companies they acquired, how is that different from buying solutions as needed and integrating them?

Mergers and acquisitions (M&A) allow successful companies to expand their market share and capabilities. Sometimes, these acquisitions are just a way to get more clients and the purchased products are discontinued if they don’t live up to the acquiring brand’s standards. When the acquiring brand is looking to expand their features and capabilities, resources are dedicated to incorporate products under one seamless, fully branded experience. In the case of the latter, the solutions purchased are almost always top-tier products (otherwise it would usually make more sense for a company to spend those resources building their own solutions). This further erodes the distinction between comprehensive solutions and “best-in-class” solutions built with a singular focus. 

Gaining access to a series of solutions under one brand umbrella also significantly simplifies the procurement process – an important benefit especially for enterprise-level clients. According to Aaron Dorsey, VP of product management, info security and privacy at Maritz, “the larger the portfolio of business on an all-in-one, the more efficiencies that are created.” 

Moreover, a single company overseeing the integration will ensure that it serves the workflows involved rather than just “playing well with others” in the sense of having an open API, which it may fall on the event organizer themselves to link together with their existing tech stack. Having to manage integrations can be really burdensome for a planning team. While most single-vertical solution providers understand the need to slot into an existing tech stack and will have built-in integrations with major event and martech staples like Salesforce or Hubspot, event organizers may need to allocate tech resources within their own team to manage these integrations – especially if the provider they’re using has not maintained their integrations as other products evolve, or if the organizer’s tech stack includes a number of smaller “best in class” solutions that don’t yet have built-in integrations with each other.

Can’t an AI Agent Just Integrate Everything Automatically?

The idea of connecting disparate systems quickly and seamlessly without the time, cost and expertise needed for human intervention sounds appealing, but it’s likely not realistic. While AI is improving all the time, there remain significant challenges when it comes to using these tools in a professional, high-stakes environment like event management. 

For one thing, these systems still require significant oversight. Event tech stacks house sensitive attendee data, high-visibility business processes and critical real-time functions. Even minor integration errors like misconfigured data syncing between a registration system and a CRM can have outsized impacts. Experienced professionals should still define the workflows, monitor the system and resolve problems when things go wrong.

Unlike traditional, vendor-maintained integrations that have been tested across thousands of client events, AI-built connections are often “one-offs,” custom-coded by the AI for a specific use case based on a given event planner’s unique tech stack and prompt instructions. That uniqueness is both the strength and the weakness of the approach: while it may meet their exact needs, it also lacks the reliability and QA processes of vendor-supported integrations.

And while there is increasing hype around “vibe coding” (generating code based on general intent rather than experienced technical precision), this is likely not appropriate for most professional applications. AI is extremely good at creating something that looks like a functioning integration, but it may miss subtle edge cases or security considerations – especially if the person vibe coding the integration doesn’t know to ask for them. Let’s say the goal is to pass attendee check-in data from an event platform to a sponsor’s lead retrieval app. A vibe coded AI might be able to create the data handoff, but does it handle throttling limits? What happens if the sponsor’s system changes its API endpoints? Does the integration respect privacy controls, such as GDPR-compliant data retention limits? Without explicit instructions, AI may not account for these nuances – and event planners will be left holding the bag.

Which brings up another challenge: responsibility. An established event tech vendor hired to build or maintain an integration is accountable when issues arise. If an organizer uses an AI agent to “auto-code” the connection, they own the results. That means they or their team must identify bugs, determine root causes and patch problems as they emerge. If something breaks mid-event, who fixes it? For most event teams – many of whom are already under-resourced as it is – this can become an impossible burden.

For mission-critical processes like registration check-in or lead capture, many feel the stakes are too high to rely on unproven solutions.

How Do Multiple Disparate Systems and Providers Impact Data Security?

Perhaps the most serious concern is security. Event tech systems typically handle personally identifiable information (PII) such as attendee names, email addresses and payment details. Trusting an AI agent to create data flows without strict security oversight raises real risks, like integrations that expose sensitive data unintentionally or a failure to comply with GDPR, SOC2, or ISO standards. Inexperienced users may not understand how to set up granular role-based permissions, which can potentially give systems more access than they should have.

But even if an organizer doesn’t attempt to integrate separate systems themselves with AI, simply having too many providers can entail special risk considerations. According to a report by cybersecurity firm Thalus, 80% of enterprise data is “scattered across file shares, cloud storage, collaboration platforms and legacy systems” that are difficult to track, leading to an increased risk of attacks, data breaches and compliance violations.

According to Nick Shirk at Fintech firm Jack Henry & Associates, part of the reason for this is a straightforward relationship between a tech stack’s complexity and a team’s ability to manage the risk across it. “Besides increased risk, this approach also results in higher costs – both at the point of initial integration and in ongoing maintenance expense.” The choice to use multiple providers puts the security onus on the event organizer while simultaneously making the task much harder and more complicated.

Similarly, DataGuard lists the “reliance on third-party services and software” as one of the biggest issues in cybersecurity. Every additional vendor increases the “attack surface,” or the points of entry attackers can use to gain access to sensitive event data. In general, minimizing the number of these “dependencies” can “reduce the potential attack vectors.” The article recommends auditing the code of all third-party solutions, but many organizers don’t have the necessary resources or expertise. A reputable provider like Stova will thoroughly audit them in order to maintain various industry-standard security credentials so event organizers don’t have to.

As a trusted tech provider assumes the responsibility of managing data security within its own products, centralizing oversight can have a number of benefits for them and for the planner. According to Shirk, each vendor within a multi-provider tech stack has less visibility and less of a holistic sense of the security from one integration to the other, which results in a less secure environment on the whole. Moreover, because they can only be held responsible for their own involvement and the processes they manage, there is less accountability in the event of an incident.

Here’s a strong conclusion you could use to wrap up the article:

Conclusion

The debate about whether to invest in an end-to-end event tech platform or a series of best-in-class tools has been going on for at least a decade, but AI is reshaping the terms of that conversation. While niche providers can sometimes deliver specialized depth, they often lack the resources, feedback loops and data sets to evolve at the pace of larger, more comprehensive platforms. Meanwhile, mergers and acquisitions, coupled with AI-driven innovation, have made many end-to-end solutions as robust, connected and feature-rich as best-in-class solutions.

Event organizers must also consider the ease of use and management of their tech stack. At least for now, AI does not erase the integration problem. In fact, an attempt to rely on AI agents to bridge disparate systems may introduce new challenges around oversight, accountability and security – challenges most event teams are ill-equipped to manage. While managing multiple providers inevitably expands the “attack surface” for sensitive attendee data, consolidating with a trusted platform places accountability, compliance and accountability in the hands of a single partner.

Ultimately, the decision comes down to risk tolerance and operational efficiency. If the priority is reducing friction, safeguarding attendee data and leveraging AI responsibly, the case for an end-to-end provider is stronger than ever. 

By centralizing not only features but also security and support, solutions like Stova enable event organizers to focus on outcomes rather than integrations. 

To learn more about how to simplify your workflow and maximize your data security, book a demo.