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AI Project auditing - identifying ROI and validating possibilities

Rahat Yasir
Oct 26 ∙ 2 mins
AI Project auditing - identifying ROI and validating possibilities

This quick article clarifies our AI Auditing phase.

Goal

According to a recent survey from Statista, “only 15% of enterprises are using AI as of today, but 31% are expected to add it over the coming 12 months”. Osedea’s AI Project Auditing offering caters to organizations that need to validate their AI plan, train management and business leaders on AI and its possibilities, set up a solid AI strategy, get recommendations on AI infrastructure, or evaluate projected return on investment for AI-based endeavours.

Current market issue

There’s a lot of hype about AI these days, and almost every corporation is investing in it. Unfortunately, a significant number of AI projects come to a screeching halt before getting into production. This happens due to unrealistic expectations, an unpracticed AI application development approach, unsustainable infrastructure, and a lack of understanding of the proper AI application development lifecycle.

Our approach

Osedea’s AI team will collaborate with the client team to understand their process, review their infrastructure and AI plan, and go through their data to find out what is possible to achieve and what is unrealistic.

AI Auditing Week Timeline

Day 1

A two-hour interactive workshop on AI business cases, AI application development life cycle, AI integration approach, and AI market trends - along with Q&A. For a quick overview of this workshop, here's our latest webinar introducing AI for business leaders.

Days 2 and 3

Client shares requirements & sample data, Q&A to understand objectives, data definition, and discussion of data format/amount, available infrastructure, and end goal.

Day 4

Osedea’s team evaluates sample data, reviews the approach, and breaks down the overall requirements with proper justifications.

Day 5

Osedea presents an overall end-to-end solution that is technically feasible and cost-effective. Limitations, proposed quick wins, and different phases of the development process are discussed.

Expected Outcomes of the AI Project Auditing process

  • Day-long workshop and presentation on AI for business leaders, IT teams, and executives
  • Data review to flag issues with data
  • Process review: dividing requirements into incremental iterations
  • Based on the data and process review, compile a list of possible AI applications
  • Define complexity, timeline, and resources needed in different AI applications for short- and long-term planning
  • Help set up a robust AI strategy for the organization
  • Collaborate with the client’s business leaders to create an AI roadmap
  • Provide recommendations on AI infrastructure and architecture, in order to incorporate AI with existing systems
  • Provide necessary guidance for the IT team to maintain future AI products and infrastructure
  • Return on investment and production-graded AI application development planning