In Cisco’s 2024 AI Readiness Index, 97% of senior business leaders said the urgency to deploy AI-powered technologies has increased in their company within the past six months. However, only 13% of companies have the AI readiness to leverage AI fully and that number has actually declined from 14% in 2023.
What has caused this disconnect in AI readiness? How are enterprises becoming less prepared for AI? Why is it so important to perform an AI readiness assessment before embarking on AI projects?
With the increased pressure to deploy and see results from AI, many companies are trying to run before they can walk. Most enterprises lack key foundational and operational capabilities and only 30% of organizations have comprehensive AI policies and protocols. Without a solid foundation of AI maturity, the majority (70%) of AI projects fail.
Meanwhile, the goalposts keep moving further away. New advancements in AI increase business opportunities but also increase the data and infrastructure requirements for AI. Enterprises that chase the newest opportunities without first increasing their AI readiness will continue to fall behind.
Why We Created the AI Readiness Assessment
Many companies jump into AI for the wrong reasons, often driven by fear of missing out, without first assessing their readiness. According to Humberto Moreira, Gigster’s Principal AI Solutions Engineer, this leads to costly missteps. “Some invest in AI without the right data, which can produce unreliable insights. Others overlook infrastructure needs, making integration with existing systems a challenge. And too often, organizations rush into production without a clear strategy, resulting in flashy demos that fail to deliver real business impact.”
A structured assessment helps businesses avoid these pitfalls. Humberto emphasizes that an AI readiness assessment is essential, as it provides a clear evaluation of an organization’s strengths and gaps across key areas like data, skills, technology, and strategy. “By identifying these early, companies can take targeted steps to solidify their foundation, launch proof-of-concept projects, scale AI into production, or optimize existing implementations.”
This is why Gigster created the AI Readiness Assessment and made it freely available on our website. Now, any enterprise can gain the insights needed to make informed, strategic AI investments that maximize value and minimize risk.
Key Areas to Perform an AI Readiness Assessment
We’ll now walk you through the five key areas of AI readiness that every enterprise should understand before starting AI development.
- Technology and Infrastructure: This assesses your organization’s ability to handle AI workloads, scalability, network capabilities, and compute resources. The growth in AI has caused major demand for GPUs and other key infrastructure. Currently, 54% of organizations have only moderate or limited infrastructure scalability.
- Data Readiness: This evaluates the quality, accessibility, and governance of data for AI use. According to Cisco, 81% of organizations have data in silos across their organization, limiting its accessibility for AI.
- Strategy and Vision: How clear are your AI goals across the organization and how aligned are they with your business objectives? While 95% of organizations have a defined AI strategy, only 41% have metrics for measuring AI impact.
- People and Skills: Workforce readiness, including training, change management, and talent acquisition, is a major factor in how successful your AI initiatives are. Only 43% of employees feel their organization manages change well, down from 60% in 2019.
- Existing AI Projects: The final area evaluates your current AI initiatives and their alignment with your organization’s overall strategy. How successful is your current AI use and how prepared are you to scale?
Is your organization ready for AI?
Levels of AI Readiness
Once you’ve evaluated the key areas of AI readiness, you’ll likely find yourself at one of four levels of AI readiness. Understanding your current level creates a clear path forward for building an AI foundation and preparing your organization for AI.
AI Readiness Level 1: Preparation and Exploration
At this level, your organization shows an interest in artificial intelligence, but lacks key foundational elements to successfully implement AI. Organizations at this stage should focus on internal preparation, including:
- Data Quality and Accessibility: The Data Science Hierarchy of Needs presents a framework for understanding your data quality, accessibility, and potential for us in AI and machine learning. Before focusing on artificial intelligence, first aim to create a data-driven organization.
- Technical Infrastructure: A majority of companies’ in-house network capabilities are not scalable or adaptable to handle complex AI projects and high data volume. Also, 94% of companies have concerns about data protection with generative AI applications.
- Stakeholder Buy-in: Work to get initial buy-in from organizational stakeholders so you can identify strategic priorities to target with AI. The entire organization needs to be on board and prepared to make foundational changes to adapt to AI.
AI Readiness Level 2: Pilot and Experimentation
Your organization has established a solid foundation for AI implementation and is ready to explore more practical applications through a proof-of-concept (POC). The right POC project should involve a single business function, or about 5-10% of the business.
To discover and prioritize AI opportunities, begin by examining your company’s larger strategic priorities, potential bottlenecks, and industry trends. 63% of companies prioritize improving the efficiency of systems, processes, and operations through AI. Next, rank the potential of these AI opportunities based on their ROI, stakeholder buy-in, and your ability to successfully seize this opportunity based on your data readiness, AI maturity level, and developer resources.
While data infrastructure and people skills were already improved in the first level of AI readiness, there is still room for optimization.
A successful POC at this stage will validate AI’s business value and drive support for future transformation.
AI Readiness Level 3: Production and Scale
Once you have demonstrated AI’s value through successful POCs, you’re ready to scale these solutions into production. While 34% of enterprises are building an initial proof-of-concept, only 14% are in the production stage of AI.
Moving from experimentation to stabilization is the pivotal point in the AI value curve where AI becomes pervasive in the organization and starts to present true value.
Successfully taking AI from POC to production requires scaling technology, implementing ML Ops, and optimizing processes. Cost-effectiveness, organizational impact, and change management will also play a major role in success at this stage.
AI Readiness Level 4: Optimization and Expansion
Companies at this level of AI readiness are in the 13% that are fully prepared to leverage artificial intelligence and take their production to the next level. They demonstrate AI maturity with multiple successful productions and a strong foundation across all key areas.
Organizations at this level are well-positioned to explore cutting-edge applications and turn AI into a major competitive advantage. At this stage, organizations should focus on more complex challenges and expand AI’s impact.
No matter what level your organization is at, conducting an AI readiness assessment is a crucial step in understanding your current needs and potential. AI readiness is a clear guide to help prioritize AI opportunities and understand the foundational, operational, and transformational changes needed to fully embrace the technology.
Take Gigster’s free, 10-minute AI Readiness Assessment today to better understand your organization’s AI maturity and create a roadmap for future advancements. You’ll save money, guaranteed, by ensuring you're fully prepared before making significant AI investments.
If you're looking for hands-on guidance in navigating AI adoption, we can help. At Gigster, we've developed a workshop designed to define a practical AI adoption strategy with a clear roadmap. We've spent hundreds of hours working with companies to build a proven framework that helps leaders assess their current AI state and plan their next initiatives—without costly missteps.
Get in touch at sales@gigster.com to learn how we can support your AI journey.
