Your expert for questions
Frauke Schleer-van Gellecom
Partner at PwC Germany
Tel: +49 175 6970 969
Email
Generate measurable value with AI across your value chain
Many organisations are aiming to transform their value creation with AI. In practice, however, few manage to realise clear, tangible business benefits. A core challenge is that numerous data and AI initiatives are launched, but they are rarely aligned or coordinated.
In many cases, AI only delivers its full potential when the entire value chain is considered, different approaches are properly integrated, and true differentiation is created. We help you embed AI across your value chain in a way that genuinely moves the needle and strengthens your market position for the long term.
“The era of vague AI experiments is over. Companies must implement value-chain-wide AI use cases that clearly set them apart from the competition.”
What sets PwC’s AI along the Value Chain services apart
What’s holding you back? Barriers to value-creating AI
Rapid advances in artificial intelligence are driving a paradigm shift that touches almost every step of the value chain. Yet AI’s broad applicability does not make its implementation easier. In many organisations, initiatives in individual business units and functions run in isolation, so synergies are lost. In some cases, leadership teams are not aligned on the strategic direction.
The sheer range of possibilities can also obscure which investments in data and AI capabilities will generate the greatest value in the short, medium and long term. Where previous data and AI investments have delivered an unclear return, there is often considerable hesitation around further spend in this area.
Systematically uncover AI’s business potential and gain clarity for execution
There is no universal recipe for successful AI deployment. Which use cases to prioritise is closely tied to your specific business context. In practice, however, proven methods exist to systematically analyse the potential of data and AI along the value chain and validate the expected ROI.
The first step is to create transparency and define strategic goals:
- Which use cases exist?
- What opportunities do they offer and how can they interlock?
- How do they support your overall strategy?
You can then identify gaps and expand your AI capabilities in a targeted way. A roadmap with clear milestones and accountabilities ultimately forms the foundation for implementation.
Turn AI experiments into business results
We support you from initial assessment through to implementation.
How we support you with AI along the Value Chain
- AI Use Case Portfolio
- AI Impact Analysis
- Feasibility Assessment
- Prioritisation of AI Use Cases
- Stakeholder Alignment
AI Use Case Portfolio
Which AI use cases sit along your organisation’s value chain and what potential do they hold? How do existing data analytics and AI initiatives fit into the broader opportunity space? A consolidated view is essential for sound investment and implementation decisions. We help you create transparency on the status quo, position use cases correctly and identify synergies.
AI Impact Analysis
A key issue for many data and AI initiatives is the lack of robust quantification of business impact. Total cost of ownership is often underestimated, or vague methods are used to determine value. We help you quantify the impact of AI solutions and use suitable KPIs to track actual value realisation over time.
Feasibility Assessment
What AI capabilities does your organisation already have? What is the skill level of your workforce? Which technical foundations are in place? We assess your AI readiness and evaluate the feasibility of new initiatives. Building on this readiness assessment, we help you close existing gaps in a targeted way so you can achieve your objectives.
Prioritisation of AI Use Cases
Which AI use cases should you implement first, and in what sequence? Prioritisation is critical to the success of any data- and AI-driven organisation, but it requires careful balancing of multiple factors – from dependencies between use cases and platforms, to budget constraints and regulatory risks. We support you with a robust prioritisation approach that reflects your specific constraints and ambitions.
Stakeholder Alignment
Because AI touches numerous business areas and functions across the value chain, a wide range of stakeholders is typically involved. We help you work with your leadership team to develop a shared strategic direction, pool resources and align all parties around common goals.
Contact us
