AI projects involve the application of cutting-edge technology to address new and often complex challenges, which inherently carries higher risks compared to projects in traditional fields. Reports indicate that the majority of difficulties in AI projects stem from the following factors:
Overinflated Expectations: Often, there are exaggerated expectations about AI’s capacity to solve specific problems and deliver a compelling business case.
Data Challenges: Challenges may arise from inadequate or low-quality data and a lack of the necessary digital channels for data collection.
Time-Consuming Training: Training and fine-tuning AI models often take longer than initially anticipated.
In response to these challenges, Tensor Bridge Invest (TBI) has developed a structured workflow designed to mitigate risks and control costs:
Step 1: Project Initiation
The customer and TBI collaboratively draft a brief description of the AI application. Duration: 1-2 short meetings.
Step 2: AI Investment Decision Course (Course 1)
TBI offers the AI Investment Decision Course, which covers a range of AI solutions, their benefits and drawbacks, investment costs, and a tailored decision tree based on the application defined in Step 1.This course provides a comprehensive understanding and an overview of key decision points.
Step 3: Pre-Study
TBI prepares a detailed pre-study document, including objectives, cost-benefit analysis, resource requirements, project timeline, cost estimates, and Go/NoGo decision points.
Step 4: Project Execution
If the project plan from Step 3 is approved, the project proceeds as planned, with regular checkpoints to monitor project progress and milestones marking key achievements.
Step 5: Training and Data Preparation (Courses 3 and 4)
If required, TBI offers Courses 3 and 4, which can expedite the training phase and data preparation when conducted at the customer’s site.
Step 6: Acceptance Testing
Comprehensive acceptance tests, including performance and stress tests, ensure the AI system meets the specified criteria.
Step 7: Ongoing Support
TBI provides follow-up support until the AI system is fully functional and integrated into the business operations.
Please note that the workflow may include additional steps if it involves computation infrastructure (training units and data interface) or if intellectual property goals, such as patents, are integral to the project. Feel free to contact us for more information in these cases.
By following this structured workflow, AI projects can be better managed and aligned with business objectives, minimizing risks and ensuring successful outcomes.