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Finance for a sustainable future:

From AI tools to AI toolboxes

In recent years, Finance organizations have increased their use of AI for both traditional and sustainability data needs. But, as data complexity grows, aligning disparate AI tools through a coordinated platform approach—not as a literal, physical IT architecture, but as an organizing principle—can help streamline data management, enhance data reliability, and unlock broader enterprise value, enabling AI to deliver benefits beyond Finance and Sustainability functions.

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AI evolves quickly

An organization’s plan for using it should keep pace. Instead of simply recasting established processes, new tools should contribute to enterprise value in new ways. When disparate use cases give way to a coherent platform approach, AI can help transform Finance and the business around it.

Three stages of AI integration

From meeting minimum requirements to building a program that sets the standard for others, each stage of AI integration can help Finance teams not only achieve but also advance in an evolving digital ecosystem.

Survive

Simply having a plan is progress

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Drive

Engaging leaders and advancing operations

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Thrive

Drive greater value without driving costs

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Common benefits of a platform approach:

Streamline data management

Integrate data gathering, transformation, analysis, and reporting across the enterprise

Enhance data quality

Increase data integrity, traceability, and stakeholder trust while reducing assurance risk

Unlock value through AI

Extend the benefits of sustainability data to support operations, supply chain resilience, and enterprise efficiency

Improve decision-making

Swiftly turn high-volume data into actionable insights, enabling better and faster decision-making

Boost productivity and user experience

Unify tools and capabilities into a single platform, increasing productivity and making it easier for users to access what they need

Support scalable AI

Facilitate the adoption and governance of evolving AI technologies, enabling adaptation and growth around changing needs

Using AI for sustainability

Areas to explore:

1. Target Setting: Visioning, benchmarking, science-based targets

2. Initiatives strategy: Research, optimization, incentives

3. Planning and analytics: Scenario planning, performance analytics

4. Initiatives program management: Enterprise performance management, enterprise risk management

5. Initiatives execution: Vendors, partners, change management, virtual power purchase agreements

One platform, endless possibilities

When a company brings all its AI efforts together, it can focus on unified goals instead of individual team needs, and transform the organization into one that can unleash the full power of AI across all corners of the enterprise. By taking a coordinated platform approach, disparate AI cases can be integrated to make an impact far greater than the sum of its parts.

Ready to unlock new possibilities with an AI platform?

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