Are you on the bench or trying to steal home from third? Organizations that realize artificial intelligence (AI) will be part of their competition and competitive advantage or disadvantage are getting on base now.

Building a Strong Foundation for AI: The Role of CFOs in Leveraging Data for Competitive Advantage

The integration of AI into business operations is rapidly transforming industries. But for AI to be effective, it needs a solid foundation: good data. CFOs play a pivotal role in ensuring organizations collect high-quality data and use it strategically to unlock AI’s potential.

Don’t you hate it when your team isn’t catching up with you, let alone the market? As a Business Leader, you deserve a CFO and an executive team that pushes you and the organization. They should be coming up with ideas and opportunities. It’s not a time for skepticism and pushback. It’s also not the time to wear all the hats. Don’t neglect your growth and risk not having financial leadership, as you’ll fall behind more than ever.

You need a team with hitters. It’s a team with base runners willing to steal and slide. It’s not a market where you can walk or wait for a safe run-in. If your CFO can’t tolerate the unknown or risk – you may have outgrown them. They don’t sound like hitters or base runners to us!

But what does that mean? How can you get home with a great CFO? What will stop the businesses that neglect financial leadership and strategy from scoring and winning?

Let’s start with the data!

Why Good Data Is the Foundation for AI

Some will argue that accounting will be replaced. Bookkeeping is undoubtedly among the top ten impacted industries. Progress is also being made with contracts, audits, and even Excel.

Sadly, none of this will come as quickly as feared because even the most sophisticated businesses are on rocky and neglected foundations. Data has been plentiful for years, but it’s rarely invested in or strategized, especially in the back-of-house areas.

To cut costs, both CFOs and organizations have allowed a mess to happen. Systems are old, unsupported, or do not talk to each other. Departments drive their agendas, and there are multiple sources of the truth.

Reconciliations, reporting, and essential questions take days to address and sometimes longer. Top that off with what’s not in our complete control—compliance. Before long, the effort and attention were all on external financial reporting, ESG, tax, and the many regulatory demands we all face.

AI is only as bright as the data fed into it. Poor-quality data can lead to inaccurate insights, flawed predictions, and bad decision-making. The “garbage in, garbage out” principle highlights that without good data, even the most advanced AI algorithms cannot deliver meaningful results.

Good data must be:

1. Accurate
2. Complete
3. Consistent
4. Timely
5. Relevant

These principles sound much like the old-school principles of audit and assurance, don’t they? In other words, they’re areas that CFOs, especially those with a background in accounting, have worked with their whole careers.

For example, a construction company might collect data on materials costs, labour hours, project timelines, and safety incidents. Ensuring this data is accurate and up-to-date will be crucial for AI applications, such as predicting project delays or optimizing supply chain management. Chasing inconsistent information tracked one way in the field, and another back of the house won’t be foundational for AI. At worst, it could lead to incomplete background and dangerous insights. At best, the AI won’t be possible at all.

The CFO’s Role in Data and AI Initiatives

CFOs are more than just financial stewards; they are increasingly becoming digital transformation champions. And in the end, good data requires good technology. It’s not very likely you’ll build an accessible foundation without using systems. These days, there’s just too much volume to tackle any other way, even within simple and small businesses.

CFOs can ensure that the organization’s data strategy aligns with overall business goals and create a data culture that supports AI adoption.

At Amplify, we’ve always said you must be tech-enabled to get ahead. You can’t scale without people, processes, and technology. We’ve focused on this with each client since day one. Our CFOs have a KPI on tech use for each client to which they are assigned. Some of their other relevant KPIs include timely reporting and overall growth of the businesses they help.

We said this before our crystal ball had AI in it. While we may not have known why we were right, we are more than ever.

Our model lends itself to an increased focus on data and what we need to do to stay ahead of our clients.

Here are some key ways CFOs can contribute internally:

1. Data Governance and Quality Control
2. Investing in the Right Technology
3. Breaking Down Data Silos
4. Setting KPIs and Measuring AI Success

How AI Can Provide a Competitive Advantage for Construction Companies

Let’s look at some specific examples in the construction industry to help illustrate where a CFO can contribute.

1. Optimizing Project Timelines and Costs

AI can analyze historical project data to predict delays and cost overruns, enabling proactive measures. For example, by analyzing data on weather patterns, labour availability, and material lead times, AI can adjust project schedules dynamically to avoid downtime. This can result in lower costs and faster project completion, giving the company an edge over competitors.

2. Improving Supply Chain Efficiency

AI can optimize the supply chain by forecasting demand for materials and equipment, leading to better inventory management. With accurate demand predictions, a construction company can avoid over-ordering or under-ordering materials, thereby minimizing waste and reducing storage costs.

In both examples, the CFO created reporting to ensure that procurement, leadership, project managers, and field staff looked at the same data. They can help set the KPIs and check that the AI is used and working.

An ERP will likely be central to the data used to achieve these competitive advantages, and the CFO can lead the technology and its use.

However, what a CFO can bring to assist growth and leverage AI goes beyond the back office and inside the organization. Here are some other areas in which they can also have an impact:

1. Negotiating better terms and conditions using market data acquired from AI and comparative information from internal data
2. Streamlined due diligence in all M&A or Financing, allowing for quicker closed transactions
3. Similarly, advancing the forecasting and investor desk and business plans will advance access to capital, brand stories and employee recruitment and retention

AI-Driven Construction Strategies: Negotiation, Due Diligence, and Access to Capital

Again, it would make more sense if we had specific examples. So, let’s revisit the construction industry and see what a CFO could do.

A construction company can use AI to analyze trends in the cost of steel, concrete, and other essential materials by examining public market data and historical internal purchase records. AI can identify patterns that predict future price changes based on seasonal demand, economic conditions, and geopolitical events.

With these insights, the company could negotiate long-term contracts with suppliers when prices rise or secure volume discounts based on projected needs. By comparing supplier performance data (e.g., delivery times and quality of materials), the company can also renegotiate terms to hold vendors accountable for consistent quality and timely delivery.

Here’s a second example: A construction company looking to acquire a smaller competitor could use AI to assess the target’s financial health, project backlog, and risk factors such as unresolved legal claims or safety incidents. AI-powered tools can also cross-reference project profitability with historical project data, labour costs, and subcontractor performance to identify potential areas of concern.

With a foundation of their data, they can quickly create pro formas by comparing and merging the target acquisition and what integration could do. Reporting on cash flow projections and risk assessments could be standardized to help leadership make decisions and negotiate. The company could use AI to generate forecasts based on past project performance, current backlog, and future opportunities.

AI can also factor in external economic indicators like interest rates, regional construction demand, and government infrastructure spending plans. This level of predictive forecasting provides a more compelling case for a go or no call.

The company can close transactions faster, reduce legal and financial advisory costs, and seize strategic growth opportunities.

In an industry where agility, cost control, and strategic growth are essential, AI and good data can give construction companies a competitive edge.

Getting to Home

For CFOs and finance leaders, to be the ones who get the run—scores and wins—means embracing data-driven decision-making and fostering a culture of innovation. A CFO can be a hitter and get on base by leading these AI initiatives. From there, they can help companies position themselves for long-term success in a rapidly changing market and get the run.

So it’s not going to be a home run. The data is too complex, and the ability to score is too complex to get around the bases quickly. But a team of hitters and base runners willing to risk and slide will win the game.

The journey to AI success starts with good data, and CFOs are uniquely positioned to guide organizations on this path. As industries evolve, the ability to harness data and AI will become a key differentiator, setting leaders apart from those who fail to adapt. The rewards can be substantial for companies willing to invest in this transformation.

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