Appalachian State University Blog

Leadership is about inspiring people, driving meaningful change and shaping a compelling vision for the future. However, today’s leaders must also navigate complex details and make informed decisions backed by comprehensive data. 

When implemented strategically with high-quality information, artificial intelligence (AI) tools can become powerful allies that help leaders optimize efficiencies, synthesize complex information and develop actionable execution plans. They also can enable leaders to present compelling evidence to strengthen their influence and advocacy.

This resource guide explores how modern professionals can strategically leverage AI in leadership to enhance their effectiveness while preserving their essential human qualities that define truly exceptional leadership.

Current State of AI in Leadership: Key Statistics

Staying current with AI trends can help leaders anticipate opportunities and challenges. Below are key statistics on AI adoption, market value and workforce impact. 

AI Adoption

AI use is expanding rapidly among individuals and organizations.

• Stanford Human-Centered Artificial Intelligence (HAI), “The 2025 AI Index Report”: This research lab found that AI adoption in business is rapidly increasing, with 78% of organizations reporting they used AI in 2024 — a significant jump from the 55% using it in 2023.

• Authority Hacker, “149 AI Statistics”: According to Authority Hacker’s annual AI survey, 32.9% of businesses replaced human tasks with AI solutions from 2023 to 2024.

• Hostinger, “AI Statistics and Trends”: In 2025, Hostinger reported that about 56% of surveyed business leaders said their companies are in the early or moderate phases of AI adoption, actively exploring its most effective uses. However, 80% said they have not yet managed to scale AI across multiple functions or fully integrate it into their operations.

• Exploding Topics, OpenAI Website Traffic, Rankings and Analytics: As of mid-2025, OpenAI (owner of the well-known ChatGPT chatbot) attracts more than 1 billion visitors to its website each month.

• McKinsey & Co., “Superagency in the Workplace”: According to McKinsey, 92% of companies surveyed intend to boost their AI investments over the next three years, signaling strong confidence in its future value.

Takeaway: Adoption of AI technology is accelerating, but most organizations are still in the early stages of fully integrating it into their core operations, giving leaders a critical window of time to experiment, set standards and prepare to scale. 

Valuation and Market Growth

The AI sector spans multiple segments, each with significant market value.

• Founders Forum Group, “AI Statistics 2024–2025”: This network for founders and entrepreneurs reports estimated global values of each AI segment in 2025: 

• AI software, such as large language models (LLMs), vision and natural language processors: $126 billion

• AI infrastructure, such as chips, cloud and databases: $88 billion

• AI services, such as consulting and deployment: $50 billion

• Cloud-based AI application programming interfaces (APIs): $32 billion

• Grand View Research, “Artificial Intelligence Market Size, Share and Trends Analysis Report”: In 2024, the global artificial intelligence market was valued at $279.22 billion. It is expected to grow rapidly, reaching $1.81 trillion by 2030. The North American market accounted for a revenue share of nearly 30%.

• Based on solution: Software led the market, accounting for 35% of global revenue.

• Based on function: Operations accounted for the largest revenue share.

• Based on end use: Advertising and media accounted for the largest revenue share.

Takeaway: The AI technology market is expanding faster than most other markets, signaling that leaders who invest early in scalable tools and talent will position themselves to capture its long-term value. 

Workforce Impact and Organizational Changes

AI continues to disrupt many industries, from health care to higher education and technology. While it is challenging to accurately measure AI’s impact on the workforce, it is clear that the use of AI is eliminating some jobs and creating new ones.

• TrueUp, Tech Layoff Tracker: As of mid-2025, tech companies have seen some 460 rounds of layoffs, affecting more than 132,000 employees (an average of about 600 people laid off per day). Many companies — including TikTok, Yotpo, WiseTech Global and Atlassian — cited AI-powered automation as a key motivating factor for the layoffs.

• McKinsey & Co., “The State of AI”: This source provides statistics on AI’s impact on the workforce. 

• Over a fifth of surveyed employers using generative AI in their organizations say that automation has fundamentally affected their workflow design. 

• Twenty percent of organizations using AI expect more than half their workforce to be reskilled over the next three years as a result.

• DataiQ 2025 Survey: Between 2024 and 2025, the number of organizations investing in data and AI initiatives rose significantly — jumping nearly 20%, from 82.2% to an impressive 98.4%.

Takeaway: With the adoption of AI technology simultaneously driving layoffs and demanding large-scale reskilling at organizations, leaders face the challenge of redesigning employees’ workflows while preparing them for entirely new ways of working.

Core Strategies for Using AI in Leadership

As AI technology reshapes industries, business leaders face growing pressure not only to understand the technology but also to develop clear, effective strategies for using it. The following approaches can help leaders drive innovation, improve efficiency and maintain a competitive edge.

1. Master “Ground Truth” Analysis

Leaders evaluating AI tools must understand their “ ground truth,” that is, the verified, accurate data that was used to train these tools, which can ensure they are providing high-quality results.

Definition: 

Ground truth acts as the benchmark for correct answers, based on real evidence rather than assumptions or guesses. High-quality labels, which are the verified answers or classifications for each example, produce reliable models; biased or incomplete labels can lead to errors.

Examples:

• AI content moderation: Social media platforms rely on ground-truthed data labeled “appropriate” or “inappropriate.”

• AI hiring tool: Recruiters use AI systems trained on candidate profiles labeled “qualified” or “not qualified” or perhaps “good candidate” or “not good candidate” to improve their recruitment outcomes.

Resources:

• IBM, “What Is Ground Truth?”: This resource defines ground truth and explains its importance in building machine learning models.

• Amazon Web Services (AWS), “Ground Truth Generation and Review Best Practices for Evaluating Generative AI Question-Answering With FMEval”: This AWS blog explains how to generate and review ground truth. It also offers best practices for scaling ground truth using LLMs.

• Sigma, “Establishing Ground Truth Data for Machine Learning Success”: This source explains the parameters that leaders should consider when establishing ground truth. 

Implementation ideas: 

• Require clear documentation of how datasets are sourced and labeled before adopting AI tools.

• Establish quality assurance checks to ensure labeled data remains accurate and current.

2. Use AI for Advanced Analytics and Business Intelligence

One of the most impactful uses of AI in leadership is in advanced analytics, which turns vast amounts of data into decision-ready insights, giving leaders earlier visibility into their organization’s potential risks and opportunities.

Definition: 

AI is used in analytics to identify patterns, predict outcomes and monitor performance to strengthen an organization’s planning and risk management strategies.

Examples:

• Predictive modeling: Retailers use scenario models to forecast demand swings and optimize their inventory.

• Sentiment analysis: Companies track their customers’ feedback to flag any dissatisfaction with their products or services before it escalates. 

• Process mining: Organizations analyze system logs to uncover workflow inefficiencies.

Resources:

• N2Growth, “The 2024 Leadership Forecast: Embracing AI Driven Decision Making”: AI experts at N2Growth highlight how executives are embracing AI technology, using it to anticipate market shifts, spot emerging challenges and develop strategic responses to stay ahead.

• Infomineo, “How CEOs Leverage Artificial Intelligence for Smarter Decision Making”: Infomineo offers practical suggestions on how leaders can use AI tools to address challenges and promote innovation.

• Intellias, “AI Decision Making: What Is It, Benefits and Examples”: Intellias explains how AI tools can empower leaders to make better decisions using their real-time decision-making capabilities.

Implementation ideas: 

• Deploy modeling and predictive analytics platforms internally to test marketing strategies.

• Integrate sentiment analysis into human resources and customer experience programs.

• Build real-time dashboards that consolidate key performance indicators (KPIs) to use in executive decision-making processes.

3. Integrate AI Into Strategic Goals 

For AI adoption to succeed in an organization, its leaders’ commitment is essential. Executives who champion AI initiatives by demonstrating their importance and integrating them into the strategic vision of the organization may stay ahead of their competitors.

Definition: 

Integration means going beyond purchasing AI tools. It requires leaders to align AI initiatives with the organization’s goals, build AI literacy across teams and ensure ethical oversight of all uses of AI technology.

Examples:

• Robotic process automation (RPA): Financial institutions use RPA to handle repetitive work — such as claims processing and compliance reporting — reducing the manual workload of employees and showing that AI tools can improve their day-to-day experience.  

• AI assistants: Executives use AI assistants to streamline meetings and manage information dissemination, demonstrating the potential for everyday productivity gains.

• Governance structure: Some companies establish an AI ethics board to evaluate projects before they are rolled out.

Resources:

• Motion, “I Tested 10+ AI Personal Assistants. Here Are the Best for Home and Work”: This source offers reviews of popular AI assistants and their capabilities.

• IBM AI Academy, “Reimagine Business Productivity With AI Agents and Assistants”: This video from IBM’s AI Academy explains how business leaders can save time and money using AI assistants.

• Groco Family Office Advisors, “Transform Your Leadership: Ultimate Guide to AI Powered Leadership”: Groco offers case studies of uses of AI-driven automation tools that are enabling executives to move away from time-consuming routine tasks and focus more on strategy and innovation. 

Implementation ideas: 

• Organize AI literacy workshops tailored for leadership teams. Focus on business applications rather than technical details; leaders need to understand what questions to ask, not how to code.

• Schedule monthly briefings on industry-specific AI developments, including an analysis of competitors and emerging opportunities.

• Establish ethics and risk committees to oversee new AI projects.

• Standardize a return on investment (ROI) framework to ensure consistent evaluation across different AI initiatives.

4. Strengthen Cybersecurity With AI

As organizations embrace AI technology, leaders will face new security vulnerabilities that can be addressed using AI tools to strengthen their organization’s defenses. According to Gartner, 85% of CEOs agree that cybersecurity is crucial for business in 2025.

Definition: 

AI-powered cybersecurity systems often can detect, prevent and respond to threats faster than traditional systems.
Examples:

• Darktrace: Threat detection and autonomous response system

• SentinelOne: Endpoint protection and threat hunting tool

• Google’s Big Sleep: Vulnerability discovery tool

Resources:

• Forbes, “Innovation, Automation, and the Cybersecurity Challenges Ahead”: This article from Forbes describes the pitfalls as well as the possibilities when using AI as a foundational component of cybersecurity.

• Cyber Management Alliance, “Top 10 AI-Powered Cloud Security Tools for 2025”: This blog offers suggestions for organizations looking to use AI tools to implement cloud security systems.

• National Science Foundation, Center for Cybersecurity Analytics and Automation (CCAA): The CCAA researches the applications of automation across critical infrastructure. Its webpage highlights current research and promising advances in automation applications.

Implementation ideas: 

• Hire cybersecurity professionals with AI expertise or upskill current employees.

• Partner with proven, reputable vendors offering measurable improvements in detection.

• Track performance metrics like detection accuracy, response times, false positives and cost savings.

• Budget for continuous model updates and the integration of new threat intelligence.

Leverage AI for Transformational Leadership

The integration of AI into leadership practices represents a fundamental shift for most organizations in their operations and competitive strategy. AI adoption is accelerating, with organizations moving from limited pilot initiatives to production-scale implementations. However, given the high business costs of adopting new AI tools, executives’ commitment and a strategic vision are needed in order to fully leverage AI in leadership.

AI technology creates unprecedented opportunities for enhanced decision-making, more effective team management and more sophisticated strategic planning. Yet, at its core, leadership remains a deeply human endeavor, one that requires a genuine connection with people, a readiness to engage in meaningful work, the ability to inspire others toward shared goals and the courage to guide others through change. 

Leaders with a professional and educational foundation in leadership, such as App State Online’s Bachelor of Science (BS) in Organizational Leadership, can learn to leverage AI effectively to increase efficiencies and promote innovation. Students will learn about entrepreneurial thinking, digital literacy and how to use technology in leadership, which can equip them to balance AI’s power with human-centered principles and create thriving organizations. 

Learn more about App State Online’s BS in Organizational Leadership today.