Sixty-eight percent of CFOs expect IT and digital transformation spending to increase over the next 12 months, the highest level in 21 quarters.¹ The investment appetite is there. What is often missing from the capital case is a precise understanding of what the investment actually needs to accomplish, and the window to make foundational architectural commitments is closing faster than most finance teams realize.
IT/OT convergence is the organizing commitment behind most of what gets labeled digital transformation in manufacturing. When information technology (planning, finance, procurement, analytics) and operational technology (machinery, sensors, controllers, production systems) are unified into a single integrated architecture, the result is a production environment where data flows continuously between the factory floor and the business layer. Machines know business context. AI systems act on both operational and financial signals simultaneously. That architecture is the prerequisite for everything else: AI analytics, digital twins, predictive maintenance, supply chain synchronization.
The 2030 Benchmark Every CFO Should Know
Rockwell Automation's 2025 State of Smart Manufacturing found that factory operations are expected to be 54% AI-augmented by 2030, up from 34% today.² That benchmark is not aspirational: it reflects what is already in deployment across leading manufacturers. The organizations that arrive at 2030 with IT/OT convergence underway will be able to capture that AI upside. Those that don't will find that their AI investments run into a consistent ceiling: insufficient integrated data to operate at scale.
For CFOs, this translates into a concrete planning question: what needs to be committed to before 2030, at what investment level, and against what return horizon?
The honest answer is that IT/OT convergence is a multi-year architectural program, not a technology purchase. It requires decisions about which systems to consolidate, which vendors to commit to, how to sequence migration without disrupting active production, and how to build the governance structures that keep an integrated system operating reliably. Those decisions need to start now to be substantially complete before 2030.
The ROI Case for CFOs
The financial case for IT/OT convergence before 2030 isn't primarily about cost reduction. It's about capability: specifically, the capability to capture the AI value that the organization is already investing in.
Most organizations are already investing in AI. Only 4% of CFOs maintain a conservative AI strategy today, down from 70% in 2020, and 61% say AI agents are changing how they evaluate ROI, shifting from narrow productivity metrics to encompass cost savings, risk and compliance improvements, and revenue growth simultaneously.³ Yet Deloitte found that 66% of organizations report productivity improvements from AI already in place,⁴ while scaling those improvements enterprise-wide remains a consistent challenge across the industry. The scaling ceiling is almost always the same: fragmented data, disconnected systems, and the inability to get operational data and business context into the same decision loop.
IT/OT convergence is what removes that ceiling. When a CFO can see, in real time, how production rates are affecting order fulfillment, inventory levels, and financial performance, the quality of decisions made at the business level changes. When AI systems can act on both operational and financial signals, the efficiency gains that are currently concentrated in isolated pilots become scalable across the organization.
For manufacturers serious about 2030 competitiveness, the investment will happen. The question is whether to invest with architectural clarity, building toward a converged system, or to continue investing in point solutions that collectively fall short of the integrated capability required.
The Sequencing Decision
The CFO and CTO who have not yet aligned on an IT/OT convergence roadmap have a near-term decision to make: where does this fit in the capital plan over the next three to four years?
The answer depends on current automation infrastructure. Organizations with significant legacy OT systems face the most complex migration paths but often have the most to gain from convergence: the operational data sitting in isolated shop-floor systems represents the largest untapped AI opportunity. Organizations that are already modernizing their ERP or manufacturing execution systems have natural integration opportunities that reduce the incremental cost of convergence.
The common mistake is treating IT/OT convergence as a technology decision that can wait until the technology is more mature or more affordable. The technology is already mature enough; the bottleneck is organizational: leadership alignment, data governance frameworks, change management infrastructure. Those take time to build regardless of when the technology investment begins.
The CFOs and CTOs who align on a 2030 convergence roadmap now are not making a bet on technology. They are making a commitment to organizational capability. That capability is what positions the organization to compete as the technology landscape of 2035 and 2040 arrives.
Magruder & Company helps manufacturing and industrial leadership teams build the business case for IT/OT convergence, structure the capital commitment, and design the governance frameworks to sustain it. Visit magruder.co or reach us at customercore.co to learn more.
Magruder & Company is a practitioner-led management consulting firm specializing in organizational AI preparedness.
Sources
- Grant Thornton, CFO Survey Q1 2026. Survey of more than 230 finance leaders. Figures cited: 68% expect IT and digital transformation spending to increase over the next 12 months, the highest level recorded in 21 consecutive quarters.
- Rockwell Automation, State of Smart Manufacturing 2025 (10th annual). Global survey of more than 1,500 manufacturers across 17 leading manufacturing countries, fielded March 2025. Figures cited: 90% say digital transformation is essential to remaining competitive; factory operations expected to be 54% AI-augmented by 2030, up from 34% at time of survey.
- Salesforce, global survey of 261 CFOs. Figures cited: only 4% of CFOs maintain a conservative AI strategy today, down from 70% in 2020; 61% say AI agents are changing how they evaluate ROI, expanding from narrow productivity metrics to cost savings, risk and compliance improvements, and revenue growth.
- Deloitte Insights, 2026 State of AI in the Enterprise. Figures cited: 58% of enterprises already using physical AI including robotics and automation, projected to reach 80% within two years; 66% report productivity improvements from AI already in place.
This is part of Magruder & Company's four-part manufacturing series on physical AI preparedness. Follow the full series for analysis on IT/OT convergence, workforce transformation, and the decisions that define competitive position before 2030.