10 Step Estimation Process Sample Checklist
View our 10 Step Estimating Process Checklist. This checklist should be tuned to the individual company’s needs and suggestions.
Table of Contents
AI is no longer an experiment—it’s the defining competitive advantage. Yet, McKinsey’s 2025 AI Report shows a massive execution gap: 92% of companies plan to invest more in AI, but only 1% have reached full maturity. Employees are ready, yet leadership hesitates. This isn’t about awareness—it’s about action.
This is more than a trend—it is a fundamental market shift. Companies that adapt quickly will gain an advantage. Organizations that hesitate may fall behind.
At Galorath, we encounter this challenge regularly and understand its impact. Many leaders see AI’s potential but struggle with the question: How can we translate AI into tangible, measurable outcomes?
The Workforce Shift: AI as Both Disruptor and Job Creator
AI is not just changing industries; it’s reshaping the workforce itself. According to McKinsey, automation and AI could disrupt up to 30% of current work hours by 2030, requiring companies to rethink roles, reskill employees, and integrate AI into daily operations. ·
- Millions of jobs will shift: AI-driven automation will replace specific roles, particularly in repetitive and process-heavy functions.
- New roles will emerge: AI is expected to create significant demand for digital engineering, data science, and AI-assisted decision-making.
- The talent gap is growing: Nearly half of employees want formal AI training, but most organizations lack structured reskilling programs.
The takeaway? AI isn’t eliminating jobs—it’s redefining them. Moreover, companies that invest in AI-driven cost estimation, risk analysis, and decision intelligence are well-positioned to lead this transformation, not just react to it.
Turning AI into Actionable Insights
AI for cost estimation and decision-making is no longer experimental. Companies integrating AI-driven analytics into their workflows and business decisions can transform raw data into strategic guidance for cost engineering, risk assessment, and digital project planning.
Generic, run-of-the-mill AI tools fail because they require too much customization, lack domain expertise, and fail to deliver immediate value. Purpose-built agentic AI platforms for cost estimation and risk analysis offer immediate, relevant, actionable insights that align with industry-specific needs. Organizations applying AI in this way can:
- Ask AI in plain language and receive relevant, actionable information in seconds.
- Identify inefficiencies and improve decision-making with AI-driven insights.
- Access predictive analytics for cost estimation and risk assessment, allowing organizations to focus on speed-to-market, project viability, and corporate profitability.
From Testing to Full Implementation
Many companies remain in the early stages of AI adoption, delaying broader implementation. However, AI value is fully recognized when organizations move beyond limited pilot programs and instead choose to integrate it into full-scale operations. Industries such as aerospace, manufacturing, IT, and software development benefit from AI-driven cost estimation tools that improve forecasting and reduce uncertainty.
A significant advantage of AI is its ability to simplify complex data. Traditional models often require technical expertise, which slows adoption. When AI is designed for ease of use, leaders can engage with it conversationally, gaining immediate insights without deep technical knowledge.
Taking Action on AI
Companies that act on AI now will lead their respective markets—those that wait will struggle to keep up. Additionally, while the gap between AI investment and measurable outcomes might seem wide, results don’t take years. AI solutions purpose-built for cost estimation and decision intelligence deliver impact from day one, accelerating decision-making, improving performance, and turning data into a competitive advantage.
Other Key Insights from the McKinsey Report
AI’s impact extends far beyond automation and efficiency. The McKinsey report highlights several trends shaping the future of business and decision-making.
AI’s potential economic impact is significant. Research estimates that AI could contribute $4.4 trillion in productivity growth, creating opportunities for companies that integrate AI into their core operations. This potential is not hypothetical; organizations that effectively use AI will unlock higher efficiency and better strategic outcomes.
Leadership hesitation remains one of the biggest barriers to AI adoption. Employees are ready, but many executives remain cautious about full-scale implementation. Companies that act decisively will position themselves to take advantage of AI’s benefits while their competitors struggle to catch up.
A divide exists between generations in AI readiness. 62% of millennials (ages 35-44) feel highly confident using AI, while only 22% of baby boomers report the same. This gap suggests that younger professionals may drive AI adoption within companies. Still, organizations will need to invest in training and support to ensure adoption across all levels of the workforce.
Employees trust their employers more than outside institutions to deploy AI responsibly. 71% of employees trust their companies to implement AI safely and ethically, which is higher than their trust in universities and large technology firms. Businesses can build on this trust by ensuring transparency and accountability in AI initiatives.
Workforce transformation is another reality of AI adoption. AI is expected to displace 92 million jobs by 2030, but at the same time, it will create 170 million new roles. Organizations must plan for this shift by reskilling employees and redefining job functions to align with AI’s capabilities.
Despite the optimism, AI’s return on investment remains a challenge for many companies. Only 19% of businesses report seeing more than a 5% revenue increase from AI today, but 87% expect AI to drive revenue growth within three years. This reinforces the need for companies to shift from experimentation to execution.
The Path Forward At Galorath, we do more than track industry shifts—we analyze them to uncover meaningful trends. Our upcoming State of the Industry Report will examine the AI readiness gap and provide insights on turning AI adoption into measurable outcomes. Beyond AI, this report will explore broader industry transformations shaping decisionmaking. From advancements in cost estimation to emerging digital strategies, we will highlight the insights business leaders need to stay ahead.
The path forward is clear. Companies that integrate AI effectively will gain an advantage, while those that hesitate risk falling behind.
See AI in Action. Register for a live demo of SEERai, Galorath’s first-to-market AI solution. Leveraging four decades of cost estimation expertise, SEERai ensures AI moves beyond experimentation and becomes a fundamental driver of success.
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