Generative AI could inject trillions of dollars into the global economy by 2025. It could transform how organizations are identifying, understanding, and engaging with their customers.
Generative AI has potential to:
- Enhance customer experience and loyalty by indicating the right service to the right customer at the right time
- Improve knowledge of the customer by identifying micro-level customer segments and create a single client view
- Increase sales and marketing cost efficiency and effectiveness by automating customer service support, content generation, and sales network optimization
To fuel the customer transformation, organizations can use generative AI in 4 key ways:
With the ability to summarize, improve, handle questions, and create content, Generative AI is a versatile solution that excels in addressing a range of critical business challenges. It empowers organizations to extract deeper insights from their existing data, elevate the personalization of customer experiences, and enhance overall productivity, for example by automating content generation (from personalized emails to software code).
Generative AI summarises vast amounts of text data and generate to help organizations improve their efficiency, productivity, and decision-making capabilities. By automating the labor-intensive process of manual analysis, generative AI can save significant time and resources while providing accurate and relevant information to support business objectives.
For our Financial Services clients, we recently developed a chatbot which summarises all campaign statistics and provides insights to the end user. For more information about this project, please contact us.
Augment content creation via auto-completion, or creation of synthetic data. This enables a delivery of personalised recommendations and solutions that improve user experience as the content is tailored to an individual customer by means of image style transfers, text personalisation, or text translation.
For several Financial Services clients, we developed a self-learning campaign model and a cusotmer lifetime value model, which bases its calculation on machine learning. For more information about these projects, please contact us.
Engage with customers in human-like dialogue to automate responses to common customer inquiries and internal queries. By leveraging natural language processing algorithms and machine learning, generative AI can quickly search through large volumes of data to provide accurate and relevant answers, reducing response times and improving customer satisfaction.
Generate new synthetic content such as images, titles, or code based on user-provided instructions. This allows organisations to produce more diverse content faster and at scale, saving significant time and resources while maintaining quality standards. It also helps keep the content fresh and relevant, which is essential for engaging communication with customers.
Learn more about industry use cases
With the ability to summarize, improve, handle questions, and create content, Generative AI is a versatile solution that excels in addressing a range of critical business challenges. It empowers organizations to extract deeper insights from their existing data, elevate the personalization of customer experiences, and enhance overall productivity, for example by automating content generation (from personalized emails to software code).
There are many use cases for Generative AI that are industry specific:
Our GenAI Partners to drive usage and value
CHF 50mio.
for the futurePwC Switzerland is investing CHF 50 millions to expand and scale its AI capabilities. We want to help clients reimagine their businesses through the power of generative AI, build trust, and drive sustained outcomes. We can already bring a balanced team of global PwC consultants, data engineers, data scientists supplemented with deep domain leaders to solve your most challenging problems.
Additionally, we have a long standing relationship with key technology player including AWS, Google, and Microsoft.
Have a look at impact from recent engagements
Enterprise level GenAI strategy and use case priorisation
Challenge
The C-suite of a global life sciences company(across business & IT) are currently assessing the impact of Generative AI across their business,including identifying use cases for driving productivity and revenue.
Approach
Collaborated with leadership at enterprise and across 8 business teams (e.g.R&D,Commercial,Legal) to define & prioritize use cases.Currently finalizing strategy, demos for review with Executive Committee and BoD.
Result
Identified and prioritized across 200+ use cases. Aligned on a set of Top 6 10X ideas to pursue.
Created business case for investment and assessed impact across productivity & revenue.
Quality and governance for LLM / GenAI and AI
Challenge
AI were being developed in various pockets across functions without any central guidance resulting in inconsistent delivery and challenges tracking risks across the organization.
Approach
Established and provided a governance blueprint for the AI/ML Oversight Team, operationalized guiding principles for the future state AI/ML risk-based system lifecycle, and created AI/ML Good Practice Document for designing and deploying ethical and responsible AI(including GenAI).
Result
Provided enterprise-first guidance on Generative AI,including awareness,risks,usage guidance.
Accelerated innovation and product life cycle with optimized resource allocation,risk mitigation.
GenAI factory implementation
Challenge
The client was using an administrative level of access within the SAP system that gives a user temporary, privileged access to other user accounts.
The client aimed to improve the process for auditing utilization logs for such privileged access accounts, and reduce the instances of misuse.
Approach
Consolidated disparate data from different systems raw data.
Automated classification and recommendation on how to proceed for each log.
Result
Reduced manual effort and time spent by the log reviewers (e.g., approximately 20% of logs with low sensitivity can be auto approved*)
Reduced number of interactions between the reviewers and privileged access account users.
Intelligent voice analytics in Wealth Management
Challenge
At the client, ~70% of RM‘s time was spent on administrative tasks such as meeting preparation, documentation and risk & compliance task. The client wanted to increase RM‘s client time by applying state-of-the-art technology.
Approach
Demonstrated the solution’s capability of recording and transcribing as well as producing high quality analytics on customer conversations.
Result
Client benefited from having summary notes and next best actions being populated after each meeting. This significantly reduced time spent by employees and helped improve compliance oversight.
Intelligent voice analytics in Wealth Management
Challenge
The client operates globally and sales and marketing campaign activities are run heavily decentralised and budgets are assigned to different teams across the globe. Client wanted to have an easy way to track spendings, efforts and campaign statuses centrally.
Approach
Set up a chatbot that provides all campaign information and statuses globally.
Result
Client is able to track all spendings, efforts und status of the globally run marketing campaigns.
Contact us
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