AI expert in business practice
qualification ‘AI-Transformation of Business Processes’ from the International Alliance of Professional Business Elite - IAPBE
Are you worried that the future is technology and that artificial intelligence (AI) can replace human labour?
We invite you to a special meeting that will change your perception of how AI can become your ally in work, freeing up time for more important tasks.
We invite you to a special meeting that will change your perception of how AI can become your ally in work, freeing up time for more important tasks.
This complex course covers key aspects of implementing artificial intelligence in business, from everyday use to deep transformation of business models. Participants will gain practical skills and theoretical knowledge on how to use AI to improve productivity, optimise business processes, develop specialised AI agents for accounting and law, and assessment of ethical aspects and risks.
Who it is for:
- Accountants, looking to optimise calculations and routine tasks.
- Lawyers, who want to improve the efficiency of analysing documents and contracts.
- Top managers, looking for new tools to organise and manage projects.
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Promowebinar:
Artificial Intelligence for your professional development
Artificial Intelligence for your professional development
12.12.2024 | 17.00 UTC+2
At the event you will learn:
- How AI is already helping accountants, lawyers and managers to automate routine processes - from report writing to legal review of documents.
- What tasks AI can take on so you can focus on strategically important projects.
- A practical demonstration of ChatGPT: see how this technology can speed up your day-to-day work and improve the accuracy of tasks.
- Real-world examples of how AI can be used in the workplace that you can incorporate into your own work.
Key topics of the meeting:
The fundamentals of large language models and their application to business.
How AI will change everyday tasks, and why it won't replace you, but will make your job easier and more efficient.
Real examples of automating processes and documents - from financial reports to legal contracts.
This event is a promotional meeting for an AI course that will teach you how to integrate artificial intelligence into your everyday work processes. Join us to learn how technology can make your job easier and you a more competitive professional!
Become a participant
Fill in the form and a specialist will contact you to clarify all details.
Programme
After the training, participants will be able to use AI to optimise business, develop specialised AI solutions, analyse business models and create innovative strategies.
Day 1-2: The basics of AI and its application to business
- Lecture:
-Definition of AI and key concepts
-History of AI development and current state of AI development
-Overview of the main AI trends: machine learning, deep learning, natural language processing
-Examples of successful application of AI in business
- Practical session:
-Analysis of cases of AI applications in different industries
-Group discussion of potential applications of AI in the participants' companies.
- Homework: Prepare a presentation on potential applications of AI in the chosen industry.
Day 3: Fundamentals of working with AI assistants
- Lecture:
-Overview of popular AI assistants (GPT-4, DALL-E, Midjourney)
-Principles of work and possibilities of modern AI models
-Ethical aspects of using AI assistants
- Practical session:
-Introduction to the interface and functionality of GPT-4
-Performing basic tasks using an AI assistant
- Homework: Development of a series of prompts to solve a business problem using GPT-4.
- Lecture:
-Definition of AI and key concepts
-History of AI development and current state of AI development
-Overview of the main AI trends: machine learning, deep learning, natural language processing
-Examples of successful application of AI in business
- Practical session:
-Analysis of cases of AI applications in different industries
-Group discussion of potential applications of AI in the participants' companies.
- Homework: Prepare a presentation on potential applications of AI in the chosen industry.
Day 3: Fundamentals of working with AI assistants
- Lecture:
-Overview of popular AI assistants (GPT-4, DALL-E, Midjourney)
-Principles of work and possibilities of modern AI models
-Ethical aspects of using AI assistants
- Practical session:
-Introduction to the interface and functionality of GPT-4
-Performing basic tasks using an AI assistant
- Homework: Development of a series of prompts to solve a business problem using GPT-4.
Day 1-2: Using AI for data analysis and reporting
- Lecture:
-Overview of AI tools for data analysis
-Automisation of data collection and processing using AI
-Data visualisation using AI tools
- Practical session:
-Working with automated analytics platforms (e.g. DataRobot, H2O.ai)
-Creating automated reports using AI
- Homework: Prepare an analytical report using AI tools
Day 3: AI in project management and planning
- Lecture:
-Overview of AI tools for project management
-Automisation of routine tasks of a project manager
-AI in resource prediction and optimisation
- Practical session:
-Working with an AI assistant to create project plans
-Automisation of reporting and communication in the project
- Homework: Developing a project plan using AI tools
- Lecture:
-Overview of AI tools for data analysis
-Automisation of data collection and processing using AI
-Data visualisation using AI tools
- Practical session:
-Working with automated analytics platforms (e.g. DataRobot, H2O.ai)
-Creating automated reports using AI
- Homework: Prepare an analytical report using AI tools
Day 3: AI in project management and planning
- Lecture:
-Overview of AI tools for project management
-Automisation of routine tasks of a project manager
-AI in resource prediction and optimisation
- Practical session:
-Working with an AI assistant to create project plans
-Automisation of reporting and communication in the project
- Homework: Developing a project plan using AI tools
Day 1-2: Predictive analytics using AI
- Lecture:
-Overview of machine learning techniques for predictive analytics
-Collection and training of data for predictive models
-Quality assessment and interpretation of model results
- Practical session:
-Working with tools for building predictive models (e.g. scikit-learn, TensorFlow)
-Building and evaluating a simple predictive model
- Homework: Develop a predictive model for a specific business scenario
Day 3: AI-based decision support systems
- Lecture:
-Architecture of decision support systems
-Integration of AI into decision-making processes
-Ethical aspects of using AI in critical decisions
- Practical session:
-Designing a decision support system
-Development of a conceptual model of a system using AI
- Homework: Creating a prototype of a decision-making panel with AI elements
- Lecture:
-Overview of machine learning techniques for predictive analytics
-Collection and training of data for predictive models
-Quality assessment and interpretation of model results
- Practical session:
-Working with tools for building predictive models (e.g. scikit-learn, TensorFlow)
-Building and evaluating a simple predictive model
- Homework: Develop a predictive model for a specific business scenario
Day 3: AI-based decision support systems
- Lecture:
-Architecture of decision support systems
-Integration of AI into decision-making processes
-Ethical aspects of using AI in critical decisions
- Practical session:
-Designing a decision support system
-Development of a conceptual model of a system using AI
- Homework: Creating a prototype of a decision-making panel with AI elements
Day 1-2: Robotic Process Automation (RPA) and Intelligent Process Automation (IPA)
- Lecture:
-Definition and principles of RPA
-The concept of IPA as a combination of RPA, AI and ML
-The advantages of IPA over simple RPA
-Examples of successful IPA implementation in different industries
- Practical session:
-Overview of popular platforms: UiPath, Blue Prism, Automation Anywhere
-Designing an IPA solution for a specific business process
- Homework: Creating a detailed IPA implementation plan to optimise a specific business process
Day 3: Digital twins and the Internet of Things (IoT)
- Lecture :
-Concepts of digital twins and IoT
-The synergy of digital twins and IoT to optimise processes
- Practical session:
-Developing the concept of a monitoring system based on IoT and digital twins
-Discussion of data analysis and decision-making techniques
- Homework: Prototyping a monitoring dashboard for the selected system
- Lecture:
-Definition and principles of RPA
-The concept of IPA as a combination of RPA, AI and ML
-The advantages of IPA over simple RPA
-Examples of successful IPA implementation in different industries
- Practical session:
-Overview of popular platforms: UiPath, Blue Prism, Automation Anywhere
-Designing an IPA solution for a specific business process
- Homework: Creating a detailed IPA implementation plan to optimise a specific business process
Day 3: Digital twins and the Internet of Things (IoT)
- Lecture :
-Concepts of digital twins and IoT
-The synergy of digital twins and IoT to optimise processes
- Practical session:
-Developing the concept of a monitoring system based on IoT and digital twins
-Discussion of data analysis and decision-making techniques
- Homework: Prototyping a monitoring dashboard for the selected system
Day 1-2: Working with APIs of AI services
- Lecture (2 hours):
-Overview of popular AI APIs (e.g. OpenAI, Google Cloud AI, IBM Watson)
-Principles of integrating AI services into existing systems
-Security and scaling when working with AI APIs
- Practical session:
-Customising the development environment for working with APIs
-Creating a simple application using AI APIs
Homework: Development of a prototype business solution using the selected AI API
Day 3: Integrating an AI service into an existing process
- Lecture:
-Methodologies for assessing the readiness of a process for AI integration
-Planning and project management of AI implementation projects
-Measuring the effectiveness of AI integration
- Practical session:
-Selecting a business process for AI integration
-Creating a detailed implementation plan for an AI solution
- Homework: Preparation of a presentation of the AI integration plan for the selected business process
- Lecture (2 hours):
-Overview of popular AI APIs (e.g. OpenAI, Google Cloud AI, IBM Watson)
-Principles of integrating AI services into existing systems
-Security and scaling when working with AI APIs
- Practical session:
-Customising the development environment for working with APIs
-Creating a simple application using AI APIs
Homework: Development of a prototype business solution using the selected AI API
Day 3: Integrating an AI service into an existing process
- Lecture:
-Methodologies for assessing the readiness of a process for AI integration
-Planning and project management of AI implementation projects
-Measuring the effectiveness of AI integration
- Practical session:
-Selecting a business process for AI integration
-Creating a detailed implementation plan for an AI solution
- Homework: Preparation of a presentation of the AI integration plan for the selected business process
Day 1-2: Analysing the impact of AI on business models
- Lecture:
-Overview of classic and innovative business models
-Analysis of cases of successful transformation with the help of AI
-Methods for generating innovative ideas with the help of AI
- Practical session:
-Analysis of the current business model of a real company
-Design thinking session to create a new value proposition
- Homework: Preparation of proposals for business model transformation
Day 3: Assessment of risks and potential of new business models
- Lecture:
-Methods for assessing the risks and potential of AI transformation
-SWOT analysis, assessment of market, technological and operational risks
- Practical session:
-Doing a SWOT analysis of the developed business model
-Development of a risk map and financial model
- Homework: Prepare a presentation with an assessment of the potential and risks of the new business model.
- Lecture:
-Overview of classic and innovative business models
-Analysis of cases of successful transformation with the help of AI
-Methods for generating innovative ideas with the help of AI
- Practical session:
-Analysis of the current business model of a real company
-Design thinking session to create a new value proposition
- Homework: Preparation of proposals for business model transformation
Day 3: Assessment of risks and potential of new business models
- Lecture:
-Methods for assessing the risks and potential of AI transformation
-SWOT analysis, assessment of market, technological and operational risks
- Practical session:
-Doing a SWOT analysis of the developed business model
-Development of a risk map and financial model
- Homework: Prepare a presentation with an assessment of the potential and risks of the new business model.
Day 1-2: Identification of processes for AI optimisation
- Lecture:
-Methodologies for analysing and optimising business processes
-Criteria for selecting processes to automate and optimise with AI
- Practical session:
-Mapping key business processes
-Identifying potential areas for optimisation with AI
- Homework: Preparation of a report analysing business processes and recommendations for AI implementation.
Day 3: Process mapping for AI optimisation
- Lecture:
-Techniques for visualising business processes
-Identifying AI integration points in processes
- Practical session :
-Developing a detailed map of the selected business process
-Identifying potential AI implementation points
- Homework : Finalisation of the process map with an AI optimisation plan
- Lecture:
-Methodologies for analysing and optimising business processes
-Criteria for selecting processes to automate and optimise with AI
- Practical session:
-Mapping key business processes
-Identifying potential areas for optimisation with AI
- Homework: Preparation of a report analysing business processes and recommendations for AI implementation.
Day 3: Process mapping for AI optimisation
- Lecture:
-Techniques for visualising business processes
-Identifying AI integration points in processes
- Practical session :
-Developing a detailed map of the selected business process
-Identifying potential AI implementation points
- Homework : Finalisation of the process map with an AI optimisation plan
Day 1-2: Developing an AI implementation strategy
- Lecture:
-Key steps in developing a digital transformation strategy
-Methods for assessing an organisation's readiness to implement AI
-Creating an implementation roadmap
- Practical session:
-Analysing readiness for AI implementation
-Creating an implementation roadmap for 3-5 years
- Homework: Finalising the strategy and preparation of a presentation
Day 3: Management of changes in AI implementation
- Lecture:
-Change management models (Kotter's, ADKAR and others)
-Overcoming resistance to change and developing a digital culture
- Practical session:
-Creating a communication plan for AI implementation
-Designing a staff training and development programme
- Homework: Preparation of a detailed change management plan
Day 4: Ethical and social aspects of AI implementation
- Lecture:
-Overview of key ethical issues related to AI and automation
-Legal and regulatory regulation in the field of AI and data protection
- Practical session:
-Creating a code of ethics for AI implementation
-Assessing the social impact of automation
- Homework: Finalising a code of ethics and social responsibility plan
- Lecture:
-Key steps in developing a digital transformation strategy
-Methods for assessing an organisation's readiness to implement AI
-Creating an implementation roadmap
- Practical session:
-Analysing readiness for AI implementation
-Creating an implementation roadmap for 3-5 years
- Homework: Finalising the strategy and preparation of a presentation
Day 3: Management of changes in AI implementation
- Lecture:
-Change management models (Kotter's, ADKAR and others)
-Overcoming resistance to change and developing a digital culture
- Practical session:
-Creating a communication plan for AI implementation
-Designing a staff training and development programme
- Homework: Preparation of a detailed change management plan
Day 4: Ethical and social aspects of AI implementation
- Lecture:
-Overview of key ethical issues related to AI and automation
-Legal and regulatory regulation in the field of AI and data protection
- Practical session:
-Creating a code of ethics for AI implementation
-Assessing the social impact of automation
- Homework: Finalising a code of ethics and social responsibility plan
Module 1: Key Applications of AI in Accounting
Block 1: Automation of routine tasks using AI:
- Processing primary documents, their automatic recognition, data extraction and classification, and compliance checking.
- Matching bank statements, identifying errors, ensuring the accuracy of financial statements and optimising accounting processes.
- Compilation of reports and ensuring their accuracy and correctness, creating a reliable basis for decision-making.
Block 2: Data Analysis and Anticipation:
- Identifying anomalies, errors and fraud in data.
- Prognosis and prediction of future financial results.
- Optimisation of tax levies through scenario analysis.
Block 3: Improving the efficiency of the accountant's work:
- Personalising the accountant's work
- Chatbots and virtual assistants.
- Personalising learning with AI to enhance accountants' skills.
Module 2: Practical AI tools and platforms
- Overview of popular AI tools related to or based on Excel: Excel with AI features, Google Sheets, Tableau, Power BI.
- Platforms for developing AI models: TensorFlow, PyTorch, Scikit-learn.
- Integrating AI into accounting systems and adding AI modules to existing accounting systems: ERP, CRM and others.
- An overview of the best AI tools for accounting that already exist in the world: from algorithms to accurate books of accounts
Module 3: Using AI to improve efficiency and for decision making
- Forecasting financial performance.
- Optimising tax payments.
- Risk assessment.
- Cost optimisation.
- AI in receivables and payables management.
Module 4: Ethical Aspects of AI in Accounting
- Transparency and explainability of AI models.
- Regulatory frameworks for AI that require transparency of models.
- Data security and privacy.
- Accountability for decisions made by AI.
Module 5: Risks of implementing AI in the accounting profession
- The cost of implementing AI and its justification.
- Resistance to change on the part of employees.
- The need to upgrade the accountant's skills towards digitalisation
- Risk from absolute automation and dependence on technology
Practical tasks
- Processing primary documents: AI is able to automatically recognise and classify various documents (invoices, cheques, delivery notes), extract the necessary information from them and enter it into the accounting system.
- Bank statement matching: AI can automatically match bank statements with internal data, identify discrepancies and suggest options to resolve them.
- Reporting: AI can automate the process of primary accounting reporting, reconciliation and tax return preparation.
- AI in accounts receivable and accounts payable automation: AI can automate routine tasks such as: sending payment reminders, generating reports on debts, analysing reasons for delayed payments, classifying customers by risk level.
- Development of a chatbot to answer typical accountant's questions.
Block 1: Automation of routine tasks using AI:
- Processing primary documents, their automatic recognition, data extraction and classification, and compliance checking.
- Matching bank statements, identifying errors, ensuring the accuracy of financial statements and optimising accounting processes.
- Compilation of reports and ensuring their accuracy and correctness, creating a reliable basis for decision-making.
Block 2: Data Analysis and Anticipation:
- Identifying anomalies, errors and fraud in data.
- Prognosis and prediction of future financial results.
- Optimisation of tax levies through scenario analysis.
Block 3: Improving the efficiency of the accountant's work:
- Personalising the accountant's work
- Chatbots and virtual assistants.
- Personalising learning with AI to enhance accountants' skills.
Module 2: Practical AI tools and platforms
- Overview of popular AI tools related to or based on Excel: Excel with AI features, Google Sheets, Tableau, Power BI.
- Platforms for developing AI models: TensorFlow, PyTorch, Scikit-learn.
- Integrating AI into accounting systems and adding AI modules to existing accounting systems: ERP, CRM and others.
- An overview of the best AI tools for accounting that already exist in the world: from algorithms to accurate books of accounts
Module 3: Using AI to improve efficiency and for decision making
- Forecasting financial performance.
- Optimising tax payments.
- Risk assessment.
- Cost optimisation.
- AI in receivables and payables management.
Module 4: Ethical Aspects of AI in Accounting
- Transparency and explainability of AI models.
- Regulatory frameworks for AI that require transparency of models.
- Data security and privacy.
- Accountability for decisions made by AI.
Module 5: Risks of implementing AI in the accounting profession
- The cost of implementing AI and its justification.
- Resistance to change on the part of employees.
- The need to upgrade the accountant's skills towards digitalisation
- Risk from absolute automation and dependence on technology
Practical tasks
- Processing primary documents: AI is able to automatically recognise and classify various documents (invoices, cheques, delivery notes), extract the necessary information from them and enter it into the accounting system.
- Bank statement matching: AI can automatically match bank statements with internal data, identify discrepancies and suggest options to resolve them.
- Reporting: AI can automate the process of primary accounting reporting, reconciliation and tax return preparation.
- AI in accounts receivable and accounts payable automation: AI can automate routine tasks such as: sending payment reminders, generating reports on debts, analysing reasons for delayed payments, classifying customers by risk level.
- Development of a chatbot to answer typical accountant's questions.
Stage 1: Project Definition and Planning
- Selecting a project topic related to the implementation of AI in the business
- Team formation (if applicable)
- Develop a project plan and identify key milestones
Stage 2: Analysis and Research
- Conduct market research and analyse existing solutions
- Defining project requirements and constraints
- Selecting appropriate AI technologies and tools
Stage 3: Conceptualisation and Prototyping
- Develop a conceptual model of the AI solution
- Creating a prototype or layout of the solution
- Initial testing and iteration
Stage 4: Performance and Risk Assessment
- Develop a methodology for evaluating the effectiveness of the AI solution
- Conduct risk analysis and develop mitigation strategies
- Evaluate cost-effectiveness and scalability potential
Stage 5: Preparation of presentation and documentation
- Create a project presentation
- Preparation of supporting documentation (technical description, implementation plan)
- Rehearsal of presentation
Final project presentation and feedback
- Presentation of projects to the expert committee
- Receiving feedback and recommendations on further development of the project
- Selecting a project topic related to the implementation of AI in the business
- Team formation (if applicable)
- Develop a project plan and identify key milestones
Stage 2: Analysis and Research
- Conduct market research and analyse existing solutions
- Defining project requirements and constraints
- Selecting appropriate AI technologies and tools
Stage 3: Conceptualisation and Prototyping
- Develop a conceptual model of the AI solution
- Creating a prototype or layout of the solution
- Initial testing and iteration
Stage 4: Performance and Risk Assessment
- Develop a methodology for evaluating the effectiveness of the AI solution
- Conduct risk analysis and develop mitigation strategies
- Evaluate cost-effectiveness and scalability potential
Stage 5: Preparation of presentation and documentation
- Create a project presentation
- Preparation of supporting documentation (technical description, implementation plan)
- Rehearsal of presentation
Final project presentation and feedback
- Presentation of projects to the expert committee
- Receiving feedback and recommendations on further development of the project
Sample International Document for the UK IAPBE Program
"AI Expert in Business Practice"
"AI Expert in Business Practice"
Speakers
- Ivan Turcan
Managing Partner of CROWE TURCAN MIKHAILENKO S.R.L.
An experienced lawyer with extensive experience in various legal fields
He started his career in 2009 working at Brodsky Uskov Looper Reed & Partners and has since held important positions in prestigious institutions.
- Tetiana Honcharenko
Owner of the group of companies ‘The Owners’
Owner of ‘Paragraph’ Social Consulting since 2012
Director of business development at ‘European Profiles’
PR expert team lead of Deinstitutionalisation Project 2017-2019
Over 11 years of experience in community management, building innovative teams, and strategic consulting.
JCI Ukraine National president 2016
Fundraiser of a number of charitable thematic and national projects totalling over $8 million
Investment expert, CEO of Founders League Investment office
Member of the Supervisory Board of Zezman holding, advisor to the CEO
- Anton Spiridonov
PhD in Computer Science
Heads the digital practice at Crowe, which supports and facilitates digital transformation, including the implementation of AI automation in business.
CO-Founder of GoodWIll biz/ Coordinates the implementation of hyper-automation technologies, including systems with AI elements
Price
800€
120£
After training there is an opportunity to pass an international exam and receive a British IAPBE diploma
Become a programme student
Fill in the form and a specialist will contact you to clarify all details
ABOUT US
ALTERRA is an international centre for business methodology and professional development. The company specializes in training on national and international certification programs, online examinations, business qualifications and issuance of international diplomas and certificates.
ALTERRA also plays a role in the creation of professional standards for accounting, tax, finance, audit, and management.
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- About 10,000 international exams
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