Transforming finance with AI: The role of orchestration and alignment

Businesses are prioritizing integrated data, stable workflows, and outcome-driven AI use cases. But across industries, what’s truly creating results is orchestration—how agentic architecture, data, and workflows are coordinated across the finance function and beyond. Here’s why top performers are pulling ahead, how they’re doing it, the role enterprise applications are playing, and how you can avoid stalled investments.

Key Takeaways 

• Industry leaders are creating true value from orchestration—taking strategic steps to build layers on top of existing systems, processes, and decisions.

• Many organizations are facing challenges in achieving desired outcomes from AI and finance transformations due to a lack of integrated, aligned systems and governance frameworks.

• By rationalizing tech stacks, prioritizing trusted data integration, and leveraging existing platforms like OneStream, NetSuite, Salesforce, and Blue Yonder, businesses can achieve true ROI with targeted AI use cases.

As organizations invest heavily in intelligence, they’re often layering it onto systems they no longer trust, raising a fundamental question: why do operations remain outdated, fragmented, and manual? Most organizations don’t lack ambition or tools, but are missing two critical elements—systems that are integrated, aligned, and capable of communicating with one another, and the expertise to orchestrate this configuration of their architecture.

Companies aren’t seeing their AI investments turn into faster financial closes, better strategic decisions, or sustainable cost takeout—particularly amid transactions, digital transformations, and increasing regulatory pressure. For many businesses, although AI may forecast cash flow or revenue, finance teams are still reconciling numbers across multiple systems and Excel files, preventing insights from being trusted and close cycles from improving.

By prioritizing AI adoption, many finance functions are overlooking strategic alignment. To achieve transformation outcomes and optimize operations, senior decision-makers must bridge the gap between their infrastructure and their data strategy.

Why modern finance still underperforms despite AI adoption

Embedding AI workflows into production undoubtedly helps organizations scale, but technology alone cannot resolve foundational inefficiencies. Most companies have not fixed their underlying data quality and governance issues before moving into production. According to a recent report by Celigo, three in four mid-to-large organizations already have an AI workflow fully in production. However, core finance outcomes like close, reporting, forecasting, and compliance still lag behind expectations.

Simultaneously, the regulatory environment is tightening. Boards, auditors, and regulators are significantly increasing their scrutiny of responsible AI usage. By 2028, 80% of CFOs are expected to mandate formal AI governance frameworks in their transformation engagements.

Finance leaders are caught between the intense pressure to adopt new technologies and the risk of moving too fast. This tension peaks during critical periods of transaction readiness and value realization, finance and ERP transformations, technology and data modernization programs, and cost takeout and operational efficiency initiatives.

Closing the alignment gap in finance technology 

AI is facilitating the rapid evolution of technology, data architecture, and operating models, but at completely different speeds. While modern tools are constantly advancing, the gap to companies’ data readiness, transaction readiness, process stability, governance and control frameworks, and organizational ownership and accountability is consistently growing. For example, when a company recently purchased AI licenses for internal staff but didn’t have sales subscription data normalized or accessible within systems, teams were left unable to analyze or automate pertinent data with AI tools until foundational alignment issues were addressed.

Gartner predicts that over 40% of agentic AI projects will be canceled by the end of 2027 due to escalating costs, unclear business value, and inadequate risk controls. Organizations suffering from an alignment gap typically exhibit a few common symptoms. Common symptoms experienced by organizations experiencing an alignment gap include:

• AI pilots that can’t scale to enterprise-wide deployment
• Automation being implemented without trust from end users
• Underlying needs remaining unaddressed while initiatives move forward
• Insights that can’t be explained, defined, or audited
• New tools and systems being layered onto fragmented finance stacks

Shifting from readiness to orchestration and governance

Businesses are experiencing friction in AI transformations, not due to tools, but due to challenges with orchestration and governance. The central issue is how AI is integrated, governed, and aligned to actual finance work.

Industry reports explicitly tie the success of agentic AI to integrated, trusted data. Success also requires stable, automated workflows alongside user adoption and clear governance and controls. Without these essential foundations, initiatives inevitably stall in the pilot phase or introduce avoidable risk.

Rationalization is key in driving business value. By reducing redundancy, clarifying ownership, and orchestrating workflows across platforms, businesses can yield significantly better results than by solely expanding their tech stacks. Anchoring AI use cases to concrete business outcomes facilitates strategic alignment, directly driving cost takeout, operational productivity, and long-term durability.

Maximizing the value of your enterprise tools

Although tools are not the core problem stalling companies’ AI initiatives, leaders can still take steps to transform their business and existing technology stack with the right partner to help support a careful, strategic approach. At Highspring, our experience across enterprise ERP, CRM, and CPM platforms provides us with a grounded view into where AI is evolving. But more importantly, we identify where these tools deliver value today versus where expectations are outpacing reality.

OneStream 

OneStream continues to heavily invest in its AI capabilities, focusing on predictive analytics and financial modeling. For your organization, this means a shift toward highly automated forecasting and scenario planning. By identifying AI use cases for variance analysis and demand forecasting in particular, finance teams can proactively adjust strategies based on real-time data integration.

What their AI roadmap looks like 

OneStream’s AI roadmap emphasizes predictive analytics and financial modeling, aligning with its mission to modernize finance.

What it means for you

For your organization, this means embracing a unified platform that integrates automated forecasting and scenario planning with real-time data insights.

Where we’ve seen AI use cases actually shine:

In practice, the most impactful AI use cases are those grounded in a company’s core operational data and tied directly to decision‑making. In one example, an organization built and deployed an AI‑based forecasting solution using internal operational data to project key business drivers. To improve forecast accuracy, the model was enhanced with relevant external indicators, enabling more precise and differentiated forecasts across regions and customer segments.

Crucially, these AI‑generated insights were not developed in isolation. Model outputs were integrated into both near‑term demand planning processes and long‑range financial plans, ensuring consistency across operational and strategic horizons. As a result, leaders were able to make better‑informed decisions and improve alignment between operational execution and financial planning. 

NetSuite 

NetSuite prioritizes automating routine accounting tasks and enhancing user experience through intelligent assistance. This empowers your teams to reduce manual data entry, streamline processes, and focus on strategic analysis. Successful AI applications in NetSuite involve automated accounts payable routing, intelligent bank reconciliations, and anomaly detection in general ledger entries.

What their AI roadmap looks like

NetSuite focuses on automating routine accounting tasks and enhancing user experience through intelligent assistance, having recently introduced additional, AI-specific offerings:

• NetSuite Next 
• NetSuite AI connector

Vendor AI roadmaps are increasingly focused on practical automation and measurable productivity gains rather than experimental use cases. For example, NetSuite’s AI strategy centers on automating routine accounting tasks and improving the user experience through intelligent, in‑context assistance embedded directly within the platform.

This focus is reflected in the introduction of AI‑specific capabilities such as NetSuite Next and the NetSuite AI Connector, which are designed to extend automation, surface insights more efficiently, and reduce manual effort across core finance and operations workflows. Together, these offerings signal a roadmap oriented toward incremental value—enhancing how users work day to day while laying the foundation for more advanced AI‑driven capabilities over time.

What it means for you 

Your organization can benefit from reduced manual data entry, streamlined processes, and a focus on strategic analysis. Highspring’s expertise ensures seamless implementation, tailored training, and a post-implementation roadmap to maximize the value of your NetSuite investment.

Where we’ve seen AI use cases actually shine

Highspring has successfully applied AI in NetSuite for automated accounts payable routing, variance analysis, intelligent bank reconciliations and reconciliation support, regression testing, automated agentic end-to-end release preview testing, and anomaly detection in general ledger entries. These capabilities have been instrumental in streamlining financial operations, as demonstrated in their work with a rapidly growing company transitioning to NetSuite for faster and more efficient financial processes.

Salesforce 

Salesforce focuses on automating workflows and enhancing agentic experiences through intelligent solutions. Successful Salesforce applications include streamlined processes, data analytics and unification, and seamless integrations across business functions.

What their AI roadmap looks like

Salesforce focuses on enabling business agility through agentic architecture, offering a suite of solutions tailored to your needs, including Sales Cloud, Service Cloud, Revenue Cloud, and Pardot. These tools are designed to optimize processes, improve scalability, and enhance user adoption through automation and data-driven insights.

What it means for you

Your organization can benefit from streamlined workflows, data clarity, and a focus on strategic growth. Highspring’s expertise ensures seamless Salesforce implementation, tailored training, and a post-implementation roadmap to maximize the value of your Salesforce investment.

Where we’ve seen AI use cases actually shine

Highspring has successfully applied Salesforce solutions to optimize process design, automate processes, and improve change management. These capabilities have been instrumental in driving business transformation, as demonstrated with a high-growth client transitioning to Salesforce for faster and more efficient CRM processes.

Celigo 

Celigo approaches AI from an integration perspective, prioritizing error handling and smart data mapping. This means fewer broken connections and significantly less manual intervention for your teams. Celigo’s AI use cases facilitate auto-resolution of integration errors and dynamic translation of complex data structures across SaaS platforms.

Blue Yonder

Blue Yonder leverages AI to optimize supply chain management and inventory planning. For technology leaders, this translates to reduced working capital requirements and higher service levels. As an award-winning Blue Yonder partner, Highspring has seen these tools drive results in predictive demand sensing and automated inventory replenishment, with algorithms analyzing thousands of variables to recommend optimal stock levels across global distribution networks.

What their AI roadmap looks like

Blue Yonder leverages AI to optimize supply chain management and inventory planning, focusing on predictive demand sensing and automated inventory replenishment.

What it means for you 

For technology leaders, this translates to reduced working capital requirements, higher service levels, and improved operational efficiency. Highspring’s expertise ensures seamless implementation, tailored training, and flexible engagement models, including Supply Chain-as-a-Service, to maximize the ROI of Blue Yonder solutions.

Where we’ve seen AI use cases actually shine

Highspring has driven results in predictive demand sensing and automated inventory replenishment, with algorithms analyzing thousands of variables to recommend optimal stock levels. Their work with clients like RSCS has improved forecast accuracy, enhanced KPI monitoring, and standardized operations, showcasing the transformative potential of Blue Yonder’s AI-driven tools.

Business outcomes unlocked by strategic orchestration

When you establish trusted, integrated data alongside clearly defined agentic AI architecture, your business becomes more agile, unlocking faster closes and better decisions. In the Highspring Agility Index Report, we found that high-agility organizations are 4x more likely to see strategy alignment across talent, execution, and technology, and that high-agility organizations with optimized AI strategy generate 1.9x higher revenue.

Other emerging AI research reinforces this agility finding. A recent large-scale field experiment shows that firms only realize meaningful revenue and performance gains when AI is intentionally mapped and orchestrated across core business functions—unlocking firm‑level growth rather than isolated task‑level productivity improvements.

Governed AI outputs provide you with audit-ready insights and regulatory confidence. Orchestrated workflows lead to lower manual effort and significantly reduced cycle times. And by enforcing clear, outcome-driven use cases aligned with your technological capabilities, your organization secures strong ROI that can withstand inevitable platform changes. Proper alignment allows AI to actively accelerate your finance function without ever compromising security or control.

Assessing your alignment

Understanding your current level of alignment is the first step toward optimization. Ask yourself and your team the following questions: 

• What is the business outcome you are trying to achieve? 
• What is the core architecture you currently have in place? 
• How are AI-generated outputs governed and approved across the finance department? 
• Where do your AI insights rely on data spanning multiple systems, and who officially owns that integration? 
• How do your current AI initiatives directly support transactions, close efficiency, or cost takeout? 
• Can your finance team explain and defend AI-driven decisions to internal auditors or external regulators? 
• Where has your technology acquisition outpaced your operating model readiness? 
• What specific AI investments would still deliver value if your core tools changed in the next 12 to 18 months?

Run a platform-aware alignment check with Highspring

Achieving alignment with your data, systems, and AI platforms requires a trusted advisor and orchestrated integration. If your organization is struggling to scale its AI initiatives, needs training and support around solution platform orchestration (NetSuite, OneStream, Salesforce, or Blue Yonder), or is looking to secure a definitive ROI from recent technology investments, Highspring can provide flexible solutions aligned with your unique finance transformation needs.

We run practical, platform-aware alignment checks that focus on the metrics directly tied to business outcomes. Our alignment check works to:

• Evaluate orchestration across your finance systems
• Assess your governance and controls
• Determine your level of integration readiness

By focusing strictly on business outcomes, your business can successfully navigate complex digital transformations, reduce technical debt, and build a scalable infrastructure that drives future growth. Contact us today to schedule an alignment check and take the next step toward achieving true AI ROI.