Consumer vs. Enterprise AI

Oct 9, 2024

2 min read

Consumer AI Tools Aren’t Built for Enterprise Needs

TL;DR: We talk with SME executives every day, and the challenges are clear: some are hesitant to adopt GenAI due to uncertainty, while others are using it but struggling to measure its business impact. The common thread? Most haven’t been introduced to AI solutions specifically designed for enterprise needs.

The future of work in industries like sports, media, and entertainment depends on adopting enterprise AI solutions. As companies embrace these technologies, those relying on consumer tools risk falling behind.

In today’s rapidly evolving tech landscape, many enterprises, especially in sports, media, and entertainment, are still using consumer AI tools—not because they’re the right choice, but because enterprise AI hasn’t taken center stage in the same way. And what’s often missed is that consumer AI and enterprise AI serve very different functions—and using the wrong set of tools can limit your company’s potential or, worse, send your data out into the ether.

So, why should this matter to sports, media, and entertainment companies? In these industries, where real-time data processing, complex workflows, and security are paramount, consumer AI tools often fall short. While consumer AI dominates public attention, enterprise AI solutions drive real results—whether it’s automating large-scale marketing campaigns or handling customer interactions across multiple platforms for all intellectual property.

According to McKinsey, companies leveraging enterprise AI report up to 66% higher productivity and 37% faster work speeds than those using consumer AI tools. Enterprise AI is built for scalability, enabling businesses to handle complex workflows and securely automate large-scale operations—capabilities that consumer AI tools lack. As AI Insider highlights, enterprise AI requires significant transformation, focusing on secure, industry-specific solutions that integrate seamlessly with existing systems. This specialization and advanced security are essential for industries like sports, media, and entertainment, where protecting intellectual property and streamlining operations are critical.

The future of work in industries like sports, media, and entertainment relies on enterprise-grade AI to meet current demands and future-proof businesses for what’s next. As more businesses embrace this technology, the gap between those relying on consumer tools and those leveraging enterprise AI will only widen.

It's time for companies to rethink their AI strategy. If you still use consumer AI for enterprise needs, now is the time to pivot.

Here are the key differences to consider when evaluating AI solutions:

Effortless Integration: Enterprise AI needs to integrate with internal and external platforms, automating workflows and ensuring smooth operations across all systems.
Enterprise-Grade Security: Protecting sensitive data is a top priority, and enterprise AI needs to offer encryption and compliance, which consumer AI lacks.
Tailored Solutions: Unlike consumer tools, enterprise AI needs to be customized for industry-specific tasks, such as media production and sports analytics.
Scalability and Ease of Use: Despite its complexity, enterprise AI must be user-friendly, allowing businesses to scale without disruption.