AI Capability Assessment

AI Capability Assessment

Unlock the Path to Successful AI Adoption
This short survey is your key to unlocking your organization's true readiness for advanced technology like AI. By assessing your strengths and gaps across critical areas like business strategy, organizational alignment, and technical capabilities, we'll provide you with a personalized roadmap to accelerate your AI initiatives.

Don't let uncertainty hold you back - take this survey and gain the insights you need to make informed, strategic decisions about your technology investments. Transform your business with confidence by understanding exactly where to focus your early AI efforts for maximum impact.

Complete the survey now and get ready to harness the full power of AI for your organization.

When do you anticipate your organization will be ready to seriously invest in and implement AI technology?*

0-6 months6-12 months> 12 months
What percentage of your annual IT/technology budget would you be willing to allocate towards AI implementation?*

> 20%10-20%0-10%
Please provide your information so we can send you your customized results*
Email*
example@example.com
Organizational Readiness
Organizational Readiness low
Your organization may not be fully prepared to successfully implement and scale AI initiatives at this time. Some suggestions to get started:

1. Conduct a comprehensive AI readiness assessment to evaluate:
* AI strategy and alignment with business priorities
* Organizational change management and risk tolerance
* Existing technology infrastructure and data maturity
* Availability of necessary skills and talent
* Risk management and governance frameworks

2. Develop a tailored roadmap and action plan to systematically improve readiness

3. Address identified gaps and challenges before embarking on impactful AI projects




Organizational Readiness neutral
Your organization has a neutral stance on many key factors related to AI readiness and adoption, suggesting some uncertainty or hesitation about moving forward with AI initiatives.

To gain clarity, confidence, and a concrete plan for AI adoption, we recommend:

1. Conduct an AI Awareness and Exploration Workshop to provide a comprehensive overview of AI technologies, facilitate discussions on specific opportunities and challenges, and identify potential pilot projects or proofs-of-concept in low-risk, high-impact areas.

2. Develop a roadmap to incrementally build AI capabilities and talent over time, aligning with your organization's strategic goals and current technological readiness.

3. Establish a cross-functional AI task force to drive initial AI initiatives, foster collaboration between business and technical teams, and ensure AI projects are aligned with broader organizational objectives.


Organizational Readiness high
Congratulations! Your organization is well-positioned to successfully implement and scale AI initiatives, with good alignment between AI efforts and business strategy.

Some suggested next steps for you to take include:

1. Develop a comprehensive AI Roadmap and Implementation Plan that:
* Prioritizes high-impact, low-risk AI use cases for initial pilots
* Outlines specific people, process, and technology investments required
* Establishes key milestones, success metrics, and a phased rollout strategy
* Identifies any remaining gaps to be addressed
* Incorporates change management strategies to engage and enable your workforce

2. Explore ways to differentiate your organization's offerings using AI-powered capabilities

3. Begin implementing your most promising AI projects to gain a significant market advantage


Data Readiness
Data Readiness low
Your organization has some steps to take to get your data ready for effective AI implementation for growth opportunities.

Some next steps include:

1. Execute a Data Audit and Strategic Planning by conducting a comprehensive assessment of the current data landscape, identifying key pain points and improvement areas, developing a phased transformation roadmap aligned with business goals, and prioritizing quick wins to build momentum.

2.Implement Robust Data Governance and Management through establishing policies and standards, empowering a cross-functional governance council, enhancing data integration and quality processes, and adopting modern data technologies for storage, processing, and analytics.

3. Build Organizational Data Capabilities by providing data literacy training across the organization, developing specialized talent, fostering a data-driven culture with defined stewardship roles, and investing in upskilling teams on new data management tools and practices.

Data Readiness Neutral
Your organization has a moderate level of data readiness, but there's room for improvement to fully support AI initiatives that will drive growth.

Some recommended next steps:

1. Conduct a Data Maturity Assessment covering:
 * Data Governance and Management
* Data Integration and Architecture
* Data Quality and Analytics
* Data Technology and Infrastructure

2. Develop a targeted roadmap to address identified gaps by establishing robust data governance practices, modernizing data architecture, and implementing advanced data quality monitoring. Additionally, focus on upskilling your team's data management and analytics capabilities while adopting the right tools and platforms to enable AI-driven insights.

3. Prioritize improvements based on their impact on AI readiness and feasibility


Data Readiness High
Your organization has a very strong data foundation in place to support successful AI implementation. Some next steps you may consider are:

1. Develop and Execute a Strategic AI Roadmap by documenting your current data landscape, identifying improvement areas, and conducting a thorough analysis of business needs to prioritize high-impact AI use cases. Create detailed business cases and implementation plans for top AI candidates, outlining a roadmap to continuously enhance data and AI capabilities.

2. Establish an AI Center of Excellence that brings together cross-functional experts to oversee AI strategy and deployment. Implement robust data management, model governance, and change management processes while providing training to equip your workforce with AI skills and literacy. This center should also oversee the exploration of advanced, enterprise-wide AI applications.

3. Build Foundations for Transformative AI by looking beyond narrow use cases to identify opportunities for enterprise-wide AI implementation. Invest in areas like predictive analytics, intelligent process automation, and AI-powered decision support, while collaborating with partners to accelerate ambitious AI initiatives. Continuously enhance your data infrastructure to support both current and future AI projects.

Governance Recommendations
Governance Readiness low
Your organization needs to establish a comprehensive AI governance framework to ensure responsible and effective AI implementation.

Ways to start:

1. Develop an AI Governance Framework that defines roles, responsibilities, and ethical guidelines while establishing an AI ethics committee to address concerns and develop policies.

2. Implement AI Compliance and Risk Management by analyzing applicable regulations, developing a compliance roadmap, and regularly assessing and mitigating risks associated with AI implementation.

3. Build AI Literacy and Capacity through organization-wide training, talent acquisition strategies focused on AI expertise, and collaboration with external AI experts to accelerate internal capabilities.

Governance Readiness neutral
Your organization has some solid AI governance measures in place, but there's room for improvement to fully support responsible AI implementation.

Some ideas to make your compliance more robust:

1. Strengthen Existing AI Governance Initiatives by assessing current structures, enhancing accountability measures, and expanding ethical guidelines to address generative AI specifically.

2. Enhance AI Compliance and Monitoring through upgrading compliance tools, developing robust monitoring systems for AI performance, and conducting regular audits to ensure regulatory compliance.

3. Foster a Culture of AI Innovation and Responsibility by encouraging cross-functional collaboration, implementing an employee contribution system for governance improvements, and establishing partnerships to stay updated on AI best practices.

Governance Readiness High
Your organization has a strong AI governance framework in place, positioning you to lead in responsible AI implementation and innovation.

Some things to consider:

Here's the consolidated version with one section of 3 action items without subitems:

Action Items:

1. Optimize and Scale AI Governance by conducting a comprehensive review of existing structures, developing strategies to scale successful initiatives organization-wide, and implementing advanced metrics to measure the effectiveness of AI governance policies.

2. Lead Industry Standards in AI Ethics and Compliance through sharing best practices, collaborating with regulatory bodies to shape future AI regulations, and implementing cutting-edge tools for predictive compliance.

3. Drive AI Innovation While Maintaining Robust Governance by establishing an AI innovation lab within the existing framework, developing an employee upskilling program on emerging AI technologies and ethics, and creating a feedback loop between development teams and governance bodies.


People Recommendations
People Readiness Low
Based on your responses, it appears that your organization needs to develop the necessary skills and staffing for AI adoption.

 Here are recommended next steps:

1. Conduct an AI Skills Gap Analysis to assess current AI-related skills across the organization and
Identifying critical skill gaps.

2. Develop an AI talent strategy combining a plan for recruiting AI specialists and data scientists along with implementing an AI upskilling program for existing employees


3. Implement AI Awareness and Education Programs
through conduct organization-wide AI awareness sessions and develop role-specific AI training modules. In addition, Implement an internal AI knowledge base and resource center


People Readiness Neutral
Your responses indicate that your organization has made some progress in developing AI skills and staffing.

 Consider these items to continue in your progress

1. Enhance AI Skills Identification and Development by refining the process for identifying AI decision-makers and early adopters and expand existing AI training programs to cover a broader range of roles

2 Strengthen AI Staffing and Resource Allocation by creating clear career paths for AI specialists within the organization and Implementing a mentorship program to accelerate AI skill development

3. Improve AI Education and best practices sharing by formalizing the role of the group responsible for AI education and creating a comprehensive set of AI best practices and guiding principles.

People Readiness High
Congratulations! Your responses suggest that your organization has a strong foundation in AI skills and staffing. To maintain your competitive edge and continue advancing your AI capabilities, consider implementing: 

1. An AI Center of Excellence which would centralize AI expertise and best practices and provide consultancy and support to all departments on AI projects

2. Implement Advanced AI Training and Development Programs. Create an internal AI certification program that emphasizes continuous learning for emerging AI technologies. In addition, establish rotational programs for AI specialists across different business units

3. Foster an AI innovation ecosystem through the creation of an internal AI startup incubator for employee-driven innovations and host AI hackathons and innovation challenges

Processes Recommendations
Processes Readiness Low
Your organization would benefit from establishing fundamental AI-related processes to support successful AI implementation and scaling.

Some ideas on how to achieve this include:

1.Establish an AI Governance and Process Framework by developing a comprehensive strategy aligned with business objectives, creating a cross-functional steering committee for oversight, and designing standardized processes for AI project selection, piloting, and scaling across the organization

2. Secure AI Funding and Resources. Conduct an AI value assessment to build a strong business case for investment. Identify quick-win AI projects to demonstrate ROI and secure further funding

3. Perform a thorough analysis of existing business processes and systems and develop an AI integration roadmap, prioritizing high-impact areas

Processes Readiness Neutral
Your organization has some AI-related processes in place, but there's room for optimization to fully support AI initiatives.

Some recommended next steps:

1. Optimize AI product/program management processes by refining existing selection and piloting processes, implementing a structured approach to scaling successful pilots, and developing key performance indicators (KPIs) to better track and communicate value across the organization.

2. Enhance AI budgeting and resource allocation by establishing a dedicated innovation fund, implementing a flexible budgeting model for rapid resource reallocation, and developing internal AI expertise through targeted hiring and upskilling programs.

3. Streamline AI integration and support by conducting an audit of current integrations to identify bottlenecks, developing a center of excellence for centralized expertise and best practices, and creating detailed integration playbooks for various AI applications, including generative AI.

Processes Readiness High
Your organization has strong AI-related processes in place, positioning you to drive innovation and lead in AI implementation.

Actions you may consider:

1. Establish an AI innovation lab to explore cutting-edge applications, develop an AI maturity model, and share best practices to position the organization as an industry leader.

2. Implement advanced AI budgeting strategies through portfolio management, AI-driven forecasting tools, and exploration of new AI-enabled business models.

3. Lead AI integration by implementing AI-driven process mining, developing a comprehensive generative AI strategy, and fostering an AI-first culture across all initiatives.

Technology Recommendations
Technology Readiness Low
Your organization should look into developing fundamental AI technology capabilities and infrastructure to support AI initiatives.

Some steps to take to support this include: 

1. Develop AI Algorithm and Model Awareness by conducting industry-relevant workshops, creating a catalog of potential AI use cases with corresponding algorithms, and establishing relationships with AI vendors to explore applicable technologies.

2. Assess and Enhance AI Infrastructure Readiness through a comprehensive audit of current technology, developing an upgrade roadmap, and implementing a pilot cloud-based AI environment for quick experimentation.

3. Build AI Integration Capabilities by cataloging existing systems to identify integration points, creating a cross-functional team for strategy development, and implementing small-scale integrations to demonstrate value and build expertise.

Technology Readiness Neutral
Your organization has some AI technology capabilities in place, but there's room for optimization to fully support AI initiatives.

Some actions to consider:

1. Optimize AI Algorithm and Model Usage by conducting a review of current models, establishing a process for evaluating new methodologies, and developing internal guidelines for selecting and implementing AI algorithms based on specific use cases.

2. Enhance AI Infrastructure Scalability through assessing current bottlenecks, implementing a hybrid cloud strategy, and developing automated scaling processes for AI applications to improve resource utilization.

3. Streamline AI Integration Processes by creating a standardized API framework, implementing a microservices architecture, and developing a center of excellence focused on best practices and reusable components.

Technology Readiness High
Your organization has strong AI technology capabilities in place, positioning you to drive innovation and lead in advanced AI applications.

Some items you may consider:

1. Drive AI Innovation and Research by establishing an AI research lab and implementing a framework for continuous experimentation with emerging AI technologies.

2. Implement Advanced AI Infrastructure Optimization through developing AI-driven management systems, exploring edge AI computing solutions, and initiating quantum computing initiatives for next-generation algorithms.

3. Lead in AI integration and ecosystem development by creating an open AI platform within the organization, developing marketable industry-specific AI solutions, and establishing a partner ecosystem to collaboratively address complex challenges.

Company Name

First NameLast Name
Should be Empty:

	Disagree	Neutral	Agree
We understand the challenges of AI adoption and have successfully implemented AI projects in our organization.
Our organization efficiently manages change and tolerates risk when incorporating new technologies like AI.
We have a standardized process for tracking and managing risks associated with new technology implementations.
Our AI initiatives align with our overall business strategy and priorities.
We have identified areas where competitors have gained advantages through AI and recognized time-consuming manual processes in our organization that could benefit from AI.

	Disagree	Neutral	Agree
We have data sources that are reliable, relevant and sufficient for AI applications
We have confidence in the accuracy of our data and it is updated regularly.
We have a clear understanding of how data is collected, managed and maintained.
We have clearly defined standards and dedicated staff for data management, data quality, data integration and data governance.
We have processes and standards outlined that will ensure the quality, privacy and security of the data used by our potential AI system.

	Disagree	Neutral	Agree
Our organization has defined accountability structures and governance roles that encompass AI authority delegation and oversight.
We have developed or are actively working on a comprehensive plan to address ethical concerns and regulatory compliance related to AI, including generative AI.
Our existing governance structure is capable of supporting and guiding transformative AI implementations across the organization.
We have implemented or are in the process of implementing tools to automate and validate compliance with AI-related policies, principles, and standards.
Our organization has a clear strategy for integrating AI governance into our overall business operations, including plans for ethical use and regulatory adherence.

	Disagree	Neutral	Agree
We have identified the decision makers in adopting and testing AI technology across the business.
We have identified the early adopters of AI in our company.
We have sufficient staff and skills available to the organization to develop, deploy and run AI applications in production.
We have the skills within our organization today to implement AI initiatives.
We have a plan for implementing training in our organization as it pertains to AI.

	Disagree	Neutral	Agree
Our organization has identified potential challenges in AI integration and has a defined approach for managing changes in industry processes and data management related to AI implementation.
We have secured budget allocation for AI pilot projects and have a team responsible for supporting, running, and maintaining AI models and tools.
Our company has established standard processes for iteratively identifying, selecting, piloting, scaling, and deploying new AI use cases, including generative AI.
We have a clear strategy for integrating AI, including generative AI, into existing business processes and systems.
Our organization has developed comprehensive support and enablement processes for AI applications, ensuring smooth adoption and utilization across the company.

	Disagree	Neutral	Agree
Our organization has explored specific AI algorithms, methodologies, or models relevant to our current and future projects, and we have identified potential integration points with existing systems.
We have the necessary technology infrastructure (hardware and software) to build and run AI applications, or we are aware of the requirements needed to develop this infrastructure.
Our technology infrastructure is optimized for AI and advanced analytics, allowing for on-demand deployment and scaling by teams running AI applications within the organization.
We have identified existing models or systems that perform functions similar to the AI solutions we are exploring, providing a foundation for further development or integration.
There is widespread awareness within our organization about the infrastructure requirements for AI applications, and we have a clear roadmap for meeting these needs.