1. Team Information

Instruction:

Provide your team name and list all team members, including their full names and departments. Ensure that each team member is eligible according to the contest rules.

Example:

• Team Name: AI Innovators
• Team Members:
  1. Maria Ivanova (Department: Marketing)
  2. Stefan Petrov (Department: IT)
  3. Ilina Dimitrova (Department: Finance)

2. Problem Statement

Instruction: Describe a real, company-specific issue you aim to solve. This could be an operational inefficiency, a process bottleneck, or any challenge that has a meaningful impact. The problem doesn’t have to be large-scale—small improvements that deliver measurable benefits are just as valuable.

Example: Our company faces inefficiencies in managing customer service requests, leading to delays in response times and unsatisfactory customer experiences. Most delays are caused by manual ticket categorization and prioritization, which takes time and can be prone to errors.

3. Proposed AI Solution

Instruction: Provide a detailed description of your AI solution, explaining how it works and how it addresses the problem. Be clear about the AI technologies or techniques (e.g., machine learning, natural language processing) involved.

Example: We propose the development of an AI-based system that automatically categorizes and prioritizes incoming customer service tickets. Using natural language processing (NLP), the system will analyze the content of each ticket and categorize it based on the issue type (e.g., technical support, billing inquiries). It will also assign priority levels based on urgency criteria, such as specific keywords or phrases (e.g., "urgent," "cannot access account"). This solution will reduce response times and allow agents to focus on high-priority tasks.

4. Implementation Plan

Instruction:

Outline a complete and detailed strategy for how your AI solution will be implemented within the company. Show how your idea will go from concept to reality. This should include specific steps for development, integration, and deployment. Consider the departments or teams affected, the resources needed (personnel, budget, infrastructure), and any training or support required. Provide a timeline for each phase and any potential risks or challenges to address.

Your plan should cover the following:

• Development Strategy: How will you build, test, and refine the AI solution before launching it? What resources will you need for this phase?
• Integration with Existing Systems: How will the AI solution be integrated with the company’s current tools and workflows? Will any systems need to be updated or replaced?
• Deployment Plan: How and when will the solution be rolled out across the company? Will it be a phased deployment, starting with certain departments?
• Training and Support: What kind of training will be provided to employees to ensure smooth adoption of the solution? Will ongoing support be required?
• Monitoring and Continuous Improvement: Show how you will track the performance of your AI solution post-implementation and make necessary improvements over time.
• Risk Management: Identify any potential challenges or risks, such as resistance to change, integration issues, or data privacy concerns, and explain how these will be addressed.

Example:

• Implementation Plan:
  
  
• Development & Testing (2 months):
  • Develop the AI model using historical ticket data from customer service interactions.
  • Perform testing and iterative refinements with a focus group of employees to ensure accuracy and efficiency.
  • Collaborate with IT and data science teams for technical support and resources.
  • The prototype will be tested in a controlled environment using historical data from previous customer service interactions. We will conduct user testing with a small group of agents to gather real-time feedback.
  • Based on the feedback, we will iterate on the design, fine-tune the NLP model, and ensure that the AI’s decision-making aligns with the company’s priorities and standards.
  • KPIs such as accuracy, speed, and agent satisfaction will be tracked during testing to measure the AI’s effectiveness.
• Integration with Customer Service Software (1 month):
  • Work with the IT department to integrate the AI-powered ticket categorization system into the company’s existing customer service software.
  • Ensure that the AI tool works seamlessly with current workflows, requiring minimal changes to the platform.
• Deployment Phases (2 months):
  • Phase 1 (Pilot): Deploy the AI solution in the customer service department, starting with a small team to evaluate real-world performance and gather feedback. Make any necessary adjustments based on team input.
  • Phase 2 (Full Rollout): Expand the solution to all customer service teams, with full integration across departments by the end of the phase.
• Training and Support (Ongoing):
  • Provide training sessions for customer service teams, teaching them how to interact with the AI system and troubleshoot basic issues.
  • Offer continuous support from the IT and AI development teams to address any problems that arise during the early stages of deployment.
• Monitoring and Continuous Improvement (Ongoing):
  • After deployment, we will regularly monitor the AI solution’s performance, focusing on key metrics like efficiency, customer satisfaction, and response times.
  • The system will undergo periodic updates to improve accuracy and adapt to new customer service challenges.
  • Feedback loops with customer service agents will be established to continually refine the AI’s performance and ensure it meets evolving business needs.
• Risk Management:
  • Integration Risks: To mitigate potential integration issues, we will perform a thorough compatibility check between the AI solution and the customer service platform.
  • User Adoption: Provide clear training and create open communication channels to address employee concerns or resistance to using the AI tool.
  • Data Privacy: Ensure compliance with company data privacy policies by anonymizing customer data where appropriate.

5. Benefits and Expected Impact

Instruction:

Detail the Benefits and Expected Impact of your AI solution. Address how the solution will improve efficiency, streamline processes, integrate into existing operations, and generate return on investment (ROI).

1. Efficiency and Productivity: Describe how the solution will improve team productivity or reduce time spent on certain tasks.
2. Process Optimization: Explain how your solution will remove bottlenecks or eliminate unnecessary steps.
3. Seamless Integration: Discuss how easy it will be to integrate the AI solution into current workflows.
4. ROI: Estimate the cost of implementation and the potential financial return or savings.

Example:

• Efficiency and Productivity:
  By automating ticket categorization and prioritization, the AI system will reduce response times by 40%, allowing agents to handle more tickets in less time.
• Process Optimization:
  The solution will eliminate the manual process of ticket sorting, allowing agents to dedicate more time to resolving customer issues and improving overall customer satisfaction.
• Seamless Integration:
  The AI assistant will be easily integrated into the existing customer service platform, with minimal disruption to current workflows.
• Return on Investment (ROI):
  The estimated cost for developing and implementing the solution is 20,000 BGN. The anticipated reduction in customer churn due to improved service levels is expected to generate an additional 50,000 BGN in revenue in the first year, resulting in a significant ROI.

6. Video Pitch (Optional)

Instruction:

If you choose to submit a Video Pitch, upload the video to the company's SharePoint platform at https://sbtsolution.sharepoint.com/. Ensure the video is accessible by the review committee. The video should be no longer than 2 minutes and clearly highlight the key points of your AI solution..

Example:

• Video Link: [SharePoint Video Link Here]

7. Additional Tips

Instruction:

• Clarity and Conciseness: Be clear and concise when describing both the problem and the solution. Avoid using overly technical jargon unless necessary to explain the AI concept.
• Use Data: Whenever possible, include data or metrics to support your claims, especially when discussing expected improvements in efficiency, productivity, or ROI.
• Collaboration: Ensure the submission reflects collaborative work, with input from all team members, showcasing different areas of expertise.