GenAI uses cases for SAGE across front, mid and back office
Commercial excellence Personalising marketing campaigns, optimising pricing strategies
as a percentage of customer operations spend
as a percentage of Marketing spend
impact as a percentage of Sales spend
Product enhancement Creating personalised products, improving product performance
efficiency gains achieved in Product and R&D across industries
Transformative revenue potential from customer-facing product innovation
Workflow improvement Streamlining key business processes, helping to manage products
efficiency gains, e.g., achieved in streamlining procurement
Software development productivity Automating code generation, improving testing processes
impact as a percentage of software engineering spend
coding speed increase1
more likely to complete tasks successfully1
Back office productivity Automating data entry, streamlining HR processes
as a percentage of Legal, Risk and Compliance spend
as a percentage of Strategy and Finance spend
as a percentage of Talent and HR spend
1. When software engineers use Amazon CodeWhisperer. Source: McKinsey & Company, The economic potential of generative AI: The next productivity frontier
Enhancing the product and commercial excellence
Product enhancement Creating personalized products, improving product performance
~14% efficiency gains achieved in Product and R&D
Insights for CFOs/ accountants
User-friendly reporting: Generate readable customized reports on most relevant metrics
Forecasting: Enhance forecasting of financial figures, e.g., demand, costs and revenues
Analysis: Generate actionable insights and play through various business scenarios
Bank flow matching (connect banks into accounting)
Double entries: Automatically detect double entries and remove them
Match: Identify categories of revenues and costs to match them to the correct categories
Benchmarking of data- economic and payroll changes
Data enrichment: Identify additional online sources and enrich benchmarking with additional data sets
Insight generation: Automatically retrieve largest drivers of payroll changes
Fraud detection (payroll, expenses, audits)
Model training: Generate synthetic data for training fraud detection models to enhance model precision
Credit card transactions: Detect atypical transactions, such as transactions conducted in foreign countries
Fraud simulations: Evaluate the effectiveness of current models and detect novel and emerging themes
Anomaly detection
Expenses: Detect duplicate entries, inflated expenses, or claims that do not align with typical spending behaviors
Accounts payable: Compare incoming invoices against historical data to identify discrepancies
Commercial excellencePersonalising marketing campaigns, optimising pricing and customer service
Targeted marketing- upselling other sage products to customers
Messaging: Sent hyper-personalized messages through channel of choice based on data-driven analysis of behaviors
Lead enrichment: Enrich lead data dynamically and prioritize based on complex set of factors
B2B sales
Account planning: Provide suggestions on areas of growth and understanding of potential churn
Pricing: Determine the optimal price for customer based on many different parameters
Customer operationsAdded by AWS
Proactive suggestions: Use data of previous interactions to more accurately address customer concern
Quality assurance and training: Review performance and generate personalized coaching suggestions
Streamlining business processes, increase software dev. productivity
Software development productivityProductivity lift of ~32% of global functional spending
Architecture: Support the design of the software architecture so that the result is more efficient and effective business scenarios
Quality control: Scan code to flag inefficiencies and security risks, generate test cases and higher quality code
New features: Automate code generation and accelerate feature development by prompts, auto-filling and completing coding statements
Workflow improvement ~18% efficiency gains
Employee wellbeing: Analyze sentiment internally and from external sources, identify patterns and trends and provide actionable suggestions
Data visualization: Preprocess data for data visualization to generate graphs, charts, tables and interactive dashboards
Knowledge management: Automating categorization and tagging of content and enhance searchability and retrieval
Back office productivity
Legal: AI analyses regulatory documents, and identifies and summarizes changes, improving compliance and reducing risk
Strategy: GenAI can automatically interpret earnings calls, compile company profiles, and analyze industry trends
HR: GenAI automatically tracks absences, promotions, payroll and can screen profiles and match them to open roles in the company
