Abdullah Omar Alkaf

To ensure successful handover plan for an AI Solution, organization need to follow the below steps: A- Documentation · Solution and Goal Overview Organization should provide a clear overview of the AI solution, including its goal, functionality, and benefits. Therefore, everyone in organization understands the goal and benefits. · Technical documentation Organization should document the technical aspects of the AI solution, including data sources, algorithms, and infrastructure. This is very important, it could need it for improvement in future. · User guide Develop a user guide that outlines how to use the AI solution, including any necessary training or support. · Maintenance guide Develop a maintenance guide/Checklist that outlines the necessary steps to keep the AI solution up-to-date and functioning correctly. Organization should consider AI Solution as any other solution like oracle or other So, they need to document all above's B- Training Provide all proper/required training to all users/operational team on how to effectively use the AI solution, including any necessary technical skills. Provide any kind of special training on how to maintain and update the AI solution. C- Performance Tracking · Develop Key Performance Indicators (KPIs) Establish KPIs to measure the AI solution's performance and effectiveness. · Monitoring and Reporting Organization should be assigned someone for monitoring, reporting, and track the AI solution's performance and identify areas for improvement. · Regular Review Organization should schedule a regular reviews to assess the AI solution's performance and make any necessary corrective action. D- Escalation Procedure Establish a clear escalation procedures for issues/concerns that arise during the use of the AI solution. Organization should assign someone for follow up AI Ticket and raised issue and take necessary actions Develop a communication plan that outlines how to communicate with stakeholders, including users, operational teams, and management. below summary illustrative

AI Agent should be updated and improved as continuous This is very important otherwise a lot of obstacles will happen during the time As one example of my current organization, we use AI agent for customer care Not only for end users but internal customers My organization uses AI Agent for all customers (employee and end user) Therefore, we need to use the feedback from all customers (employee, supervisor, end user, manager, ….etc) to improve AI Agent customer care There are a lot of mechanisms and tools like following: 1) User feedback Collect user feedback (employee, customer, manager, supervisors, experts,…etc) through surveys, ratings, or open-ended comments to understand their experiences and perceptions. 2) continuously update the KB knowledge 3) Review and use raised ticket for improve AI Agent 4) Performance metrics Track performance metrics such as accuracy, response time, and user engagement to identify areas for improvement. After we had received the feedback, Organization should be analysis, evaluate, and interpreting those feedback through : 1) Data analysis Analyze feedback data to identify trends, patterns, and areas for improvement. 2) Root Cause Analysis Conduct root cause analysis to understand the underlying reasons for issues or errors. 3) Prioritization Prioritize feedback based on impact, frequency, and user needs. 4) Frequently review After we had analysis the feedback, organization need to take appropriate action like following: 1)Model updates Update the AI model with new data to improve performance 2) Process/design improvements Implement process/design improvements 3) User Interface Changes Finally, Organization shall be always monitoring the performance and keep update AI Agent

Our company use AI Agent for customer complaint solutions My Company use some techniques to keeping AI Agent focused on target and keep always efficient My company use some of the following techniques Prompt framing - Clear, simple, and concise language Use simple and direct language in prompts to ensure the customer understands the required very easy - Specific target Clearly define the goals and objectives to keep the customer focused - relevant Information Provide relevant information to help the AI agent understand the customer's needs Design of Flow - Structured of process flow This is very important technique Design and structure of process flow that guides the customer through the process - Decision Trees should be very clear Checkpoints - Regular summaries Provide regular summaries of the conversation to ensure the customer is on track and understands the progress -Confirmation Steps Include confirmation steps to verify the customers' understanding and agreement with the next steps. Clarifying Questions - Use Open and ended Questions - Use follow up questions to confirm understanding My company can use Natural Language Processing (NLP) to analyze customer input and detect potential issues or misunderstandings Also, we can use sentiment analysis to detect the customers emotional tone In additional, we can use customer Feedbac

Prompt Design 100% will impact AI enabled take decision Therefore, The quality of prompt design will significantly influence the accuracy, tone, and trustworthiness of AI decision. In our manufacturing plant, we use prompt and by this prompt we enable AI take a decision to accept or reject any customer complaint received. So, the quality of prompt is very important in AI decision A proper designed prompt will guide the AI model to produce relevant, accurate, and unbiased responses, while a poorly designed prompt will lead to confusion, wrong, and biased responses. AI model is used to analyze any customer feedback or complaint based on prompt designed. Poor of designed Prompt can lead to one or more of the following: 1) Wrong analysis of the customer complaint or feedback 2) Reject the correct claim, this will lead customer unsatisfied 3) Accept the wrong claim, cost the organization 4) AI model might incorrectly classify the customer complaint/feedback A small changes in prompt can make a big difference like following: 1) To be specific Adding specific keywords to the prompt will help the AI model focus on specific task. 2) Tone language. 3) Use historical data and how to guide the AI model To develop good design of prompt, we can use the following guidelines: - Clearly define the task - Provide relevant context to help the AI model understand the task and produce accurate responses. - Use specific language - Test and refine the prompt design to ensure accurate response.

As example, Organization Applying AI Customer support for handling the complaint or queries over the time, there is possible to degrade silently due to many reasons like change of customer culture, customer behavior, customer skill, change of product or service regardless the reason, organization should be developing warning signs these warning signs shall alerts the organization that AI solution in not working properly some examples of warning signs 1) Tracking of performance metrics Track the metrics that was developed beginning like accuracy, speed, precise and ..etc organization should always track these metrics and take immediately action in case shift the performance 2) Monitor data input by customer or end user Organization should monitor the data input by customer and ensure consistency of dealing with data and ensure correct input data we can also use statistical tools and metric like mean, variance, and correlation 3) Monitoring data output as organization monitor the data input, also organization should monitor data output ensuring the data output is consistency organization should detect any reason cause degradation Therefore, organization need to catch the issues before causing real harm through the following 1) development automated Alerts it's difficult to manual monitoring so, organization should develop an automated alert that alerts organization if any drift or shift company can develop internal automated alerts or can use available automated platform or tool that available in marketing 2) detect non normal or drift data organization can use for example 8n8 for detect drifted data so take action immediately and evaluate AI Solution 3) Regular AI Solution assessment organization can arrange regular meetings with all concern to discuss and evaluate the AI Solution evaluate the data input and output evaluate the performance evaluate the metric evaluate all the system to ensure the suitability in many cases, organization don't need to remove the AI Solution by above action, we can enhance the AI Solution and upgrade and improve the system so organization performance will be always satisfied the objective and strategic

We had built some AI Solution/agent in our manufacture and some of them were not suitable for our process and we had decided to remove it from our process such as AI Agent for prices Our business is related to steel, and the prices of steel variety daily So, AI solution was not perfect for this process There are signs/Indicators of AI Solution Degradation in Manufacturing 1) Decreased Accuracy A decline in accuracy or performance over time, such as increased error rates or not correct results/decision. 2) Increased Complaints Increase in complaints or feedback about the AI solution's performance, such as we had received complaints from sales department regarding prices. 3) Changes in Behavior 4) Knowledge Base Drift Changes in the underlying data or knowledge base that the AI solution relies on, such as steel world prices changes. To ensure Sustainability for Long-term 1) Continuous Monitoring Continuously monitor the AI solution's performance and accuracy, using metrics such as accuracy, precision, and recall. We should take actions immediately 2) Regular Updates Regularly update the AI solution's knowledge base to reflect changes in behavior. This is very important, AI Solution should be capable to update knowledge base to reflect actual data such as in our example steel price 3) Human Oversight Implement human oversight and review processes to detect and correct errors or inconsistencies in the AI solution's performance. 4) Flexibility and Adaptability Design AI solutions with flexibility and adaptability. 5) Collaboration and Feedback Encourage collaboration and feedback between all concerns such developers, users, sales and stakeholders to identify areas for improvement and ensure the AI solution meets user needs. 6) Implement Continuous Testing Implement continuous testing and validation processes to ensure the AI solution's performance and accuracy. By following these best practices and being aware of the signs of AI solution degradation, manufacturers can contribute to ensuring the long-term sustainability of AI deployments and maximize their benefits.

A lot of companies lost their efforts/solution during Control phase No goals if efforts will be gone or shift to worse So, any company should think in control phase and how ensure sustainability by using different methods and techniques There are a lot of reasons for these shifting or slipping and the following are some of them: 1) Weak or lack of Monitoring Without regular monitoring, improvements can drift/slip over time, and issues may unnoticed. Here, company should develop robust process and procedures for monitoring the process after solutions We can use SPC, charts, using also AI platform So, company will notify early So, we correct the issue immediately 2) Insufficient Training If employees are not properly trained on new processes, procedures, & AI tools may not use them effectively/properly, and then leading to drifted/slipping. 3) Changes in Processes Company stuff should know how to deal with changes in processes 4) Lack of Accountability As mentioned above, there are a lot of tools and Techniques for Sustaining the process like following: 1) Control Charts Using SPC properly is very important. Company needs to understand the data type and select proper control charts Control charts can help monitor the process performance and detect deviations early. So, we can raise corrective action 2) Dashboards Using dashboards like power bi can provide visibility into process performance 3) Internal Audits Conduct regular internal audits is very important to ensure that processes & procedures are being followed. 4) Continuous Training Continuous training can help ensure that employees (old and new) have the skills and knowledge needed to sustain process. 5) Process Documentation/form 6) AI Platform Using AI techniques like n8n will help company to detect the deviation early 7) regular meeting Management should be always aware and should take proper actions to ensure process always in proper way By using these tools and techniques, company can sustain process over time and ensure that drifted have not appeared.

Governance, Business Excellence values, transparency, accountability, and continuous improvement shall be granted during applying AI Solution otherwise company will face a lots of problems and concerns and not comply with international standard. Currently, one of the most national standards/requirements is Governance We need to ensure well governance during applying AI Solution Therefore, we need to ensure the following during design AI Solution: 1)Transparency AI decision should be transparent, explainable, and auditable. 2) Accountability Define clear accountability for AI system performance. 3) Continuous Improvement we should always improve the design and enhance AI Solution through reviewing the process and ticket that raised by end user also, validate the suitable solution 4) Compliance Ensure that AI systems comply with government laws, regulations, and industry standards like MODON. 5) Monitoring Implement continuous monitoring and feedback mechanisms to detect issues, identify areas for improvement, and optimize AI system performance. To ensure the Governance we need to involve the following: 1) Board member 2) IT 3) Risk Management Team 4) AI Solution owners It's better to be representative from each operation department It's very important to include all operation departments Then everyone will be involved and feel responsibilities The mechanisms that need to put in place to maintain both agility and control are as follows: 1)Well-designed governance framework. 2)Risk Management Can use tool like FMEA 3)Regular Reviews 4) Enhance VSM 5) Data Analytics 6) Use Quality control tool like pareto, SPC, Fishbone,… We should always review and analysis the data Develop a new procedure for Conduct regular reviews of AI systems and governance frameworks to ensure they remain relevant and effective. 4)Training Provide advanced training and awareness programs to ensure that staff understand AI governance policies and procedures.

The specific role of business excellent Master Black Belts (MBBs) during AI-Powered Solutions that build it for critical process like customer care are the following: 1) cooperation with Process Expertise: MBBs should listen and use process expertise during the design/Mapping Because they are fully understanding operations/Process So, their recommendation/thought are very important during build AI-powered solutions for critical process 2) Setting clear Requirements for each critical process: MBBs should fully understand Objectives/key performance indicators (KPIs) for critical process and then monitoring AI-powered solutions to ensure matched the requirements and goals 3) Ensure AI Solution Alignment with business strategy: MBBs should received the approval for design/Mapping and AI Solution from the following before start/release: Key person of process excellence Key person of critical process Key person of customer care And top management MBB should explained to the organization the following so they can support him: - How AI-powered solutions can improve the following: increase efficiency reduce waste and cost enhance/improve the quality - MBB can validate AI-powered solutions and prove that Solution meets customer needs, process goals - monitoring the solution design/Mapping - provide reports and evidence for improvement using dashboard and comparison graph - can conduct survey (voice of customer) to prove the improvements for critical process

After i had completed lean six sigma with benchmark company i had started developed and implement Statistical Process control chart for the following stages: - Monitoring Receiving testing - Monitoring In Process Quality control - Monitoring Before dispatched the final Products to the customers QC Team monitoring testing/inspections records through SPC using Minitab software my issue is that some time the QC Team didn't recognize the trend or shift so production will keep continue manufacture until outliers observed after CAIPO Course we can apply n8n so we can received alerts early so i strongly recommended and i will start applying n8n for above process so, we can notify the production team early and a void the rejection

Some of Key Aspects of AI 1. Cognitive automation: Automating tasks that typically require human thought and effort. 2. Machine learning (ML): Enabling AI systems to learn from data and improve during the time. 3. Reasoning and hypothesis generation: AI solution can generate hypotheses and reason about complex problems. 4. language processing: AI systems can understand and generate human language. 5. Intentional algorithm mutation: AI systems can adapt and change their algorithms based on new data or experiences. Applications of AI AI has numerous applications across various industries, including: 1. Virtual assistants: AI-powered virtual assistants can perform tasks, answer questions, and provide recommendations. 2. Image recognition: AI-powered image recognition systems can identify objects, people, and patterns in images. 3. Predictive maintenance: AI-powered predictive maintenance systems can predict equipment failures and reduce downtime. 4. Healthcare: AI can help diagnose diseases, develop personalized treatment plans, and improve patient outcomes. 5. vehicles: AI-powered autonomous vehicles can navigate roads, avoid obstacles, and improve safety. Some The benefits of AI include: 1. Increased efficiency: AI can automate repetitive tasks and improve productivity. 2. Improved accuracy: AI can reduce errors and improve decision-making. 3. Enhanced customer experience: AI-powered chatbots and virtual assistants can provide personalized support and recommendations. 4. Innovation: AI can enable new products, services, and business models. Some of Challenges and Limitations 1. Bias and fairness: AI systems can perpetuate biases and discriminate against certain groups. 2. Transparency and explainability: AI systems can be difficult to understand and interpret. 3. Job displacement: AI can automate jobs and displace workers. 4. Security and privacy: AI systems can be vulnerable to cyber attacks and data breaches. beat regards

In my work environment, the task or activities that related to emotional and related to personnel issue will be too hard to handle it and convert it to AI AI is based on algorithm and didn't understand the emotional and critical case AI follow the instruction and KB that build it by developer. we can use AI to enhancement the routine process and job like dealing with customer, supplier, internal process and operation activities AI is powerful tool to increase the productivity and accuracy in a lots and different process making employees understand the goal of AI it will help a lots to think creativity and improve the quality