AI readiness: The essential quiz and framework for modern enterprises

For large organizations, achieving AI readiness is a complex and multifaceted journey. Investing in the latest technologies is just the beginning — the real challenge lies in integrating these technologies into the organization to deliver tangible value and drive meaningful transformation.

To help you navigate this process, we’ve developed a questionnaire and framework for assessing AI readiness. This framework offers practical insights to guide your transformation, helping you understand your organization’s current position and make informed decisions for success in an AI-driven future.

Summarized by Writer

• Achieving AI readiness involves aligning AI initiatives with business goals, building a strong data infrastructure, developing a skilled workforce, and fostering a culture of innovation and continuous learning.
• The four key categories for AI readiness are strategy, execution, innovation, and enabling capabilities, each crucial for a successful AI transformation.
• AI-ready organizations focus on identifying and prioritizing the right use cases, ensuring that AI projects are aligned with business goals and have a clear pathway to value creation.
• Execution involves guiding organizational change, fostering cross-functional collaboration, and growing talent to ensure smooth technology integration and innovation.
• Innovation and enabling capabilities include encouraging experimentation, disrupting business models, creating robust data management systems, and committing to ethical and responsible AI usage, all supported by trusted technology partners.

AI readiness for enterprise organizations is a state where the company stands fully equipped to effectively implement, integrate, and leverage artificial intelligence technologies. This involves aligning your AI initiatives with strategic business goals, building a strong data infrastructure to support AI applications, developing a skilled workforce capable of managing and optimizing AI systems, and fostering a company culture that embraces innovation and continuous learning. By achieving AI readiness, you ensure that you can adopt the latest AI technologies and derive significant value and competitive advantage from them.

The pillars of AI readiness

To achieve AI readiness, organizations must focus on four key categories: strategy, execution, innovation, and enabling capabilities. Each category is essential for a successful AI transformation.

Strategy: The foundation of AI success

The secret to AI success isn’t just advanced algorithms or powerful computers. It’s about having a solid plan in place — one that encompasses foresight, insight, vision, influence, and laser-focused use case discovery and prioritization. It’s about making sure your AI projects are marching in step with your overarching business goals, guided by data, and aimed at making a real difference.

Monitoring and identifying relevant AI trends

AI-ready organizations stay ahead by continuously scanning the horizon for new technologies and methodologies, resisting distractions from “shiny objects.” They don’t give in to hype and concentrate on solving business problems through innovation.

At apparel brand Adore Me, for example, SVP of Strategy Ranjan Roy always looks for new ways to serve customers through technology.

“Ultimately, we see generative AI in every part of the business, but we’re only starting to scratch the surface,” he says. “We can take processes that used to be writing long Excel formulas or writing lines of code and instead, with generative AI, use language to create solutions to answer specific business problems.”

Recognizing the business and cultural impact of AI

But it’s not just about technology. These organizations excel at anticipating AI’s impact on current and future customers and employees. They proactively identify opportunities to address these impacts, ensuring that AI solutions are customer-centric, employee-focused, and value-driven.

Teresa Tung, cloud first chief technologist at Accenture, emphasizes the need for both foresight and insight in enterprise AI strategy: “Understanding the true opportunity, both external-facing — how is your business going to change and thrive with the onset of generative AI because every industry is gonna be disrupted — and then also internal-facing, really seeing not just the cost, but the productivity.”

Articulating a clear AI vision

A compelling AI vision energizes and aligns teams, fostering a shared understanding of AI initiatives. This vision should guide the organization forward.

For example, personalized prescription company Curology has experienced a 50% productivity increase across various functions since adopting the Writer generative AI platform. Director of User Experience Sarah Merlin emphasizes the importance of a shared vision: “My number one goal was scalability. We’ve achieved that by focusing on strategic work rather than day-to-day tasks. We’re working smarter, not harder.”

Influencing stakeholders

Effectively influencing key internal and external stakeholders is another hallmark of AI-ready organizations. They shape future AI strategy and policy by building strong relationships and fostering collaboration. Engaging with industry leaders, regulatory bodies, and academic institutions can provide valuable insights and support.

“If business leaders actively participate in workshops, champion AI initiatives, and bring employees along through upskilling and reskilling programs, you’re on the right path,” says Writer CEO May Habib. “But if you’re unsure if you have this level of engagement, then you probably don’t.”

Discovering and prioritizing use cases

A critical starting point for the journey to AI readiness is identifying and prioritizing the right AI use cases. This strategic step guarantees that organizations invest their time and resources where there’s the greatest potential for value creation, in line with their overarching goals, and with a clear pathway to a return on investment.

Brian Flanagan, digital experience strategist at Perficient, explains, “While enterprise companies understand the need, they often don’t know how to get started and what tools will best serve them. AI use case mapping allows companies to quickly identify how AI can benefit an organization and provide measurable value, and then rapidly iterate on the findings.”

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Execution: Turning vision into reality

Executing with excellence, driving change, teaming effectively, and growing talent and impact are key to achieving AI readiness. When done well, they enable smooth technology integration, foster innovative collaboration, and help tap into the power of AI across any enterprise.

Monitoring and enabling change

AI-ready organizations excel at guiding and enabling fundamental changes in their operational methods. They create a culture of change and innovation, weaving AI initiatives into the organization’s fabric. This involves not just technological changes but also shifts in organizational culture and processes.

Collaborating across functions

Cross-functional integration is a key strength of AI-ready organizations. They unite diverse skillsets and perspectives to ensure that AI initiatives are comprehensive and well-executed. Clear communication channels and regular cross-functional meetings help ensure everyone is aligned and working towards common goals.

Camilla Sullivan, who advises global brands on change management at Navigaite, shares a best practice for overcoming barriers to AI adoption: “Involve everyone from IT staff to end-users. Secure their support by maintaining open lines of communication and encouraging two-way dialogues. This inclusive approach helps build a supportive environment for change.”

Innovation: Driving continuous improvement

Embracing innovation through experimentation, disruption, internal venturing, and partnership ecosystems will undoubtedly bolster your AI readiness. This approach nurtures a culture of ongoing improvement, empowers swift prototype and scale AI solutions, and taps into external know-how to spearhead transformative change.

Encouraging and supporting AI experimentation

AI-ready organizations cultivate a space where teams can explore new ideas and learn from successes and failures. This culture of experimentation is crucial for driving innovation and maintaining a competitive edge.

At New American Funding, Chief Marketing Officer Andrew Strickman attests to the power of creating a culture of experimentation from the top down.

He highlights the importance of top-down support for experimentation: “Often, decisions are made conservatively based on business and investment value. However, to truly understand AI’s potential for your teams, you must engage with it at a fundamental level. My advice? Play, explore, experiment, and have fun with it.”

By cultivating a safe space for experimentation and gradual adoption, organizations can build trust in AI technologies. This way their employees feel confident and capable in using AI in their work.

Disrupting business models through transformational breakthroughs

These organizations aren’t content with incremental improvements — they aim to revolutionize their operations.

At Vizient, leader in healthcare innovation, VP of AI Optimization Steve Waldon discovered that engaging non-technical stakeholders can lead to unexpected AI breakthroughs. During a hackathon, the winning idea came from a non-engineer, showing the potential of inclusive collaboration.

“This was a paradigm shift,” Waldon shares. “It demonstrated that individuals can create tools for themselves without needing a team of software engineers. This empowers people who previously couldn’t build custom solutions.”

By opening the floor to diverse perspectives and skills, organizations can find innovative solutions that fundamentally change their business operations and capabilities.

Creating robust investment and  governance models

AI-ready organizations allocate resources and support to transform innovative ideas into reality. This may include setting up internal innovation labs or partnering with startups.

An AI Center of Excellence (CoE) is pivotal in supporting AI governance by offering expertise, guidance, policy development, risk assessment, training, and collaboration. Their involvement ensures AI initiatives adhere to ethical standards, regulatory requirements, and organizational objectives. This leads to responsible and successful AI implementation and innovation.

Establishing strong governance frameworks allows organizations to navigate the complexities of AI deployment while maximizing their investment and ensuring they uphold ethical practices.

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Enabling capabilities: The backbone of AI success

Building blocks like data infrastructure, ethical frameworks, and talent development are critical for AI readiness. These elements establish the foundation for effective data management, skill-building, and collaboration in implementing AI responsibly.

Investing in and developing AI-related skills

Organizations recognize that a skilled workforce is essential for successful AI adoption. This may involve offering internal training programs, partnering with educational institutions, or hiring external experts.

A prime example of this approach is Dropbox, which has developed multiple employee training tracks to ensure their team feels confident and equipped to use AI technologies. Rachel Calabretta, manager of CX scaled content development at Dropbox, explains, “We created a safe space for those who wanted to play and experiment, but also established baby steps for people who were more timid about using AI or had anxiety about trusting it in their work. Our training and onboarding process is designed to eventually lead us to full generative adoption. We encourage everyone to explore: ‘Here’s what it can do. Feel free to go in and play and experiment. And if you’re not there yet, try this first, try this next.’”

By creating a nurturing environment for skill development, organizations like Dropbox empower their employees to embrace AI confidently. This drives innovation and enhances overall productivity.

Ensuring quality and security with a robust data management system

AI-ready organizations maintain the infrastructure necessary to collect, store, and analyze data effectively, ensuring the accuracy and reliability of AI models. This includes investing in data governance, quality, and security.

Geeta Pyne, chief architect at TIAA, stresses the centrality of data in AI transformation: “Data and metadata are interconnected, allowing AI to be applied in various contexts. Ultimately, it all comes down to the data I provide. If it doesn’t deliver business or customer value, it’s merely technology for technology’s sake.”

By investing in strong data management systems and prioritizing data quality, organizations can enhance their AI capabilities and make sure that AI serves its intended purpose — driving business value and improving customer experiences.

Committing to ethical and responsible AI usage

AI-ready organizations have established and communicated governing frameworks for responsible and ethical AI usage and development. They guarantee that AI initiatives follow ethical standards and regulatory requirements. This includes addressing issues such as bias, transparency, and accountability.

By committing to ethical AI practices and promoting transparency, organizations can mitigate risks associated with AI deployment as well as build trust among stakeholders, leading to more sustainable and successful AI initiatives.

Partnering with trusted technology providers

A reliable technology partner accelerates AI readiness by offering specialized expertise and advanced tools tailored to specific needs. They provide ongoing support and updates, helping organizations stay at the forefront of AI advancements. These partners also bring industry-specific knowledge and best practices, guiding organizations in data management, model training, and regulatory compliance. This collaboration enhances AI capabilities, aligns initiatives with business goals, and drives sustainable growth while upholding ethical standards.

By leveraging partnerships with trusted technology providers, organizations can use external expertise and resources. This enables them to navigate the complexities of AI implementation and maximize the impact of their AI initiatives.

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Writer supports organizations at any stage of the AI readiness journey

At Writer, we partner with organizations to develop their AI capabilities comprehensively. We’ve helped implement AI at the world’s top companies and have the deep conviction that only comes from having done this with hundreds of enterprises. From this experience, we’ve turned our know-how and learnings into the deepest, most battle-tested blueprint for AI program management.

By combining our proven platform with years of functional, technical, and industry experience, We help companies build those internal leaders and AI builders who become industry experts in their own right.

We help organizations create a repeatable productization and support model to scale the impact of their AI initiatives. This involves developing standardized processes and frameworks that allow successful AI projects to be replicated and expanded across various departments.

For instance, when Salesforce embarked on its journey to AI readiness, there were no established playbooks for scaling AI adoption. They turned to Writer for guidance in building AI operations capabilities. Through enterprise enablement, onboarding sessions, prompt workshops, tool training, and hackathons, we supported their team in prioritizing use cases and empowering internal champions to become AI app builders.

“The Writer team really acts as strategic advisors for us. They are instrumental in helping us achieve high adoption rates and develop internal AI capabilities,” says Annemaria Nicholson, senior manager of AI and content operations at Salesforce. “As a result, our users feel empowered to use Writer and AI Studio every day.”

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By partnering with organizations at various stages of their AI readiness journey, Writer enables businesses to actualize the full potential of AI. This drives innovation and success through expert guidance and support.

Your AI transformation starts here

The journey to AI readiness is a critical one, and it requires a strategic and comprehensive approach. By focusing on the four pillars of AI readiness — strategy, execution, innovation, and enabling capabilities — organizations can position themselves for success in the AI-first future.

Whether your organization is highly AI-ready or just starting, the right strategies and partnerships can significantly impact your journey.

Taking a proactive approach to AI readiness not only positions organizations to thrive in a rapidly evolving technological landscape but also empowers them to use AI as a catalyst for growth and innovation.

Is your organization ready for the AI-driven future?

Assessing your organization’s readiness for AI is the first step towards leveraging its transformative potential. By understanding your current capabilities and identifying areas for improvement, you can strategically position your organization to thrive in the AI-driven future.

Take our AI-readiness quiz to find out!