How Token Management can make AI projects successful?
A software services provider company understood the power of AI in software development to generate code much faster. The management of the company decided that by investing in AI, they can increase their project deliveries by 40% in a year and started adopting AI based code development as their core process. The time-to-deliver their projects reduced considerably but, the management had a big shock by the end of the year.
Their AI bill was more than 250% than the additional revenue they generated by increasing the projects they delivered using AI. The net effect was, the company revenue increased but margins shrank significantly impacting the bottom line. The AI project was considered a failure based on the overall result.
AI based software engineering and industrial engineering is increasing significantly. Enterprises have completed their AI POCs successfully but are struggling to convert these POCs into production in real world. The main reason for this situation is the ROI of the AI project. The AI tools are measured using “tokens” which is the AI standard unit of measurement, and which is used to quantify the AI usage and the final bill.
Tokenomics: The main challenge
Token economics plays a significant role in deciding the outcome of AI. Enterprises who are monitoring the token consumption by their users and AI services are able to project the yearly expenditure upfront, and adjust their IT systems and usage policies to ensure AI usage is within budget.
The main challenge for enterprises in monitoring and managing tokens is that there is no industry standard or measuring and billing tokens. Each AI vendor has a different way of token measurement based on the LLMs and models, and the pricing of tokens also varies. Hence, enterprises do not have a consistent and centralized way to monitor and manage tokens.
Veraify: Token Management
Veraify from Cloudbrink is an AI-native secure access and governance platform that gives organizations the visibility, control, and protection required to safely adopt AI across the enterprise. Veraify’s unique software-only endpoint based architecture allows the solution to monitor every AI service that user is using and in any form – native app, browser-based, plugin, assistant, API, CLI/IDE – and project the token usage across all users, AI services, departments as well as enterprise-level.
AI project admins will have insights into which departments are using tokens, which AI services have the maximum spent, which users are power users of AI, and several other insights.
Token consumption dashboard
Token consumption breakdown
Governance and Control of AI
The future of enterprise IT and Infosec systems will have a significant portion of AI services. As enterprises reap the benefits of AI, having a clear control and governance of the AI services – both sanctioned as well as unsanctioned – will enable the enterprise to take the AI advantage to the full extent.
AI cost is a critical piece of this puzzle. A unified platform like Veraify – AI Security + High-performance ZTNA + SWG + Multi-cloud networking + Digital Experience Monitoring (DEM for QoE) + Deep Visibility – is going to help the enterprises in taking control of both security and cost aspects of their AI consumption.
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