In 2024, generative AI moved from buzzword to boardroom priority. Research shows that 72% of organizations are already using GenAI in at least one business function [1]. Yet despite this surge in adoption, many enterprises find themselves struggling to translate implementation into impact.
According to BCG’s latest analysis, "of the 98% of companies that are experimenting with AI, only 26% have developed the necessary capabilities to move beyond proofs of concept and begin extracting value." [2] This gap isn't just about technology – it represents billions in unrealized potential.
What’s causing this disconnect?
The challenges for enterprise come in two flavors: organizational and technical.
On the organizational side there is changing how teams work, training staff, updating processes. This is tough but familiar. Given Digital Transformation initiatives over the past decade, enterprises have been driving this kind of change for years.
The real headache is the technical side - getting AI to do actual work instead of just generating text. This is where companies are losing money.
Let's break down why:
1. Integration Headaches
AI can't just plug into your company's existing systems. Every single thing you want AI to do – check email, update databases, send messages, check the CRM – needs custom code to make it work. Integration code is difficult in normal cases, but in this case the developer also needs to have expertise in the latest AI tool-calling techniques, worsening an already deep AI skills gap
2. Security Nightmares
When AI needs to access company systems, things get messy. Current solutions either give AI too much access (dangerous) or too little (useless). It's especially tricky when AI needs to act on behalf of different employees or customers – like checking individual calendars, sending personalized email, or looking up a support ticket.
3. Accuracy Issues
AI sometimes makes things up. That's annoying when it's writing a blog post. It's a disaster when it's handling customer data or making business decisions.
4. Even more security problems
No one wants their AI infrastructure in a public cloud. The data is too sensitive to trust to someone else’s service. Also, latency and data transfer costs can become a big problem. The future of AI infrastructure is self-hosted in VPCs.
The Cost of Waiting
While the challenges are real, the cost of inaction is existential. McKinsey's analysis suggests that early adopters of GenAI are already seeing a 10% advantage in EBIT over competitors in a very short time period. [1] This advantage compounds over time, creating an increasingly wide gap between AI leaders and laggards– put more plainly, winners and losers in every market category.
A Practical Solution
Arcade is a solution designed to overcome these obstacles and help enterprises realize the full operational potential of AI. Arcade has built the infrastructure that lets AI safely and effectively work with your existing, authenticated systems.
Here's how:
- Pre-built Connections: We've already done the hard work of connecting AI to common tools like Gmail, Slack, and Salesforce. Or need something custom? Our development kit lets you build it in minutes.
- Secure Access: Our connectors let AI safely access company systems without compromising security, i.e. we make user-based authentication dead simple. With Arcade, AI can check calendars, send emails, and query databases while respecting on behalf of the end-user, respecting existing user permissions.
- Speed and Reliability: We've optimized everything for real-world use. Actions happen in parallel when possible, and we've built in safeguards for when things go wrong.
- Accuracy Control: We've developed ways to keep AI focused and accurate, reducing those made-up responses that plague other AI systems.
- Flexible Setup: Run it in the cloud or on your servers – your choice. Especially important if you have strict security requirements.
The Bottom Line
The companies winning with AI aren't necessarily the ones with the fanciest technology. They're the ones who've figured out how to make AI do actual work. Arcade helps you join their ranks.
The gap between AI's potential and today's reality is real. But it's not permanent. With the right tools, you can start getting actual value from your AI investments.
Ready to start building your AI transformation? Contact Arcade today.
Sources:
- "The state of AI in early 2024: GenAI adoption spikes and starts to generate value" - McKinsey & Company, 2024
- "Where's the Value in AI" - Boston Consulting Group, 2024
- "LLM to ROI - How to scale gen AI in retail" - McKinsey & Company, 2024
- "Five Functions Where AI Is Already Delivering" - Bain & Company, 2024
