Skip to main content
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.
HomeResourcesWebinars

Building a Capability Roadmap for AI

Webinar

Despite the rise in excitement about adopting AI within the enterprise, many data teams today still struggle to drive value out of data & AI technologies. To successfully use AI within an enterprise, you need a range of capabilities, from data stewardship to MLOps to AI product management and even storytelling. Understanding these capabilities and how to develop them within your organization is essential to achieving your strategic initiatives around AI.

In this session, Rehgan Avon, Co-founder & CEO at AlignAI, will outline how to build a strategic roadmap any organization can adopt for developing AI capabilities and learn how to avoid common pitfalls with AI development.

Key Takeaways:

  • Understand the critical capabilities organizations need to realize value from their data and AI initiatives
  • Learn how to build a strategic roadmap to work with data and build AI effectively.
  • Learn about common challenges companies face during this process and tactics on how to avoid them.

[COURSE] Implementing AI Solutions in Business

[TRACK] AI Business Fundamentals

[CHEAT SHEET] Business Use Cases of ChatGPT

[PODCAST] From Data Literacy to AI Literacy with Cindi Howson, Chief Data Strategy Officer at ThoughtSpot

Summary

Achieving AI success in organizations requires more than just mastering AI modeling; it includes data management, MLOps, AI product management, and effective communication. Regan Avon, co-founder and CEO of Align AI, emphasizes the need for a capability plan to boost AI adoption and governance. Key challenges include aligning the organization and the difficulty of balancing people and process, which often hinder AI implementation. Regan stresses aligning AI strategy with company goals and outlines a phased approach: from strategy alignment to operational integration. She also discusses the balance between visionary approaches and technical feasibility, highlighting the need to reconcile these methods to avoid overbuilding or creating custom solutions that lack sustainability. Moreover, the webinar explores the ROI of AI initiatives, emphasizing the need to demonstrate business value and secure continuous funding. Regan also touches on adjustments to agile methodology for AI projects, the importance of change management, and the evolving role of AI teams within organizational structures. By encouraging collaboration between technical and non-technical teams, and prioritizing scalable, sustainable AI systems, companies can better manage the complexities of AI implementation.

Key Takeaways:

  • AI success depends on mastering multiple disciplines beyond modeling, including data management and AI product management.
  • Aligning AI strategy with company goals is important for realizing ROI and operational integration.
  • Balance visionary ideas with technical feasibility to avoid overbuilding or unsustainable solutions.
  • Adjust agile methodology for AI projects to account for technical nuances and feasibility assessments.
  • Encourage collaboration between technical and non-technical teams to ensure scalable and sustainable AI systems.

Deep Dives

Aligning AI Strategy with Company Goals

Re ...
Read More

gan Avon emphasizes the importance of aligning AI strategy with overall company objectives. This alignment ensures that AI initiatives contribute meaningfully to business goals such as increasing market share, launching new products, or enhancing customer service. Regan outlines a four-phase approach: starting with aligning AI strategies to company goals, prioritizing use cases, assessing AI and data feasibility, and finally operationalizing and integrating these solutions into the organization. This method not only clarifies the potential ROI but also ensures that AI initiatives are purposeful and impactful. As Regan points out, “If you can start to make business justifications on some of these use cases that are leveraging these core fundamental capabilities you’ve built, you can start to associate actual value back to the company.”

Reconciling Visionary Ideas and Technical Feasibility

One of the important discussions in the webinar revolves around the reconciliation of visionary ideas and technical feasibility in AI implementation. The visionary approach often involves innovative ideas from the business perspective without initial regard for feasibility, while the technical feasibility approach focuses on building technical capabilities. Regan emphasizes the need to balance these approaches to avoid overbuilding or creating custom solutions that are not sustainable. She suggests starting with use cases that align with company objectives and building necessary capabilities iteratively. Regan advises, “You really need to balance both... start tacking on, like, more and more of those foundational tasks and projects as you get more of these use cases pushed out.”

Adjusting Agile Methodology for AI

The webinar discusses the adjustment of agile methodologies for AI projects, acknowledging the unique challenges posed by AI’s technical nuances. Unlike traditional software development, AI projects require a significant feasibility assessment phase due to the complexity and variability of data-driven solutions. Regan discusses the difficulty of fitting data science feasibility work into typical agile sprints, highlighting, “We could spend a whole year researching to see if this problem is feasible... applying agile to that in a strict way can be really challenging.” Despite these challenges, agile principles can be adjusted to manage deployment and task solidification effectively, ensuring iterative progress and adaptation in AI projects.

Encouraging Collaboration between Technical and Non-Technical Teams

Regan Avon emphasizes the importance of encouraging collaboration between technical and non-technical teams to enhance AI adoption and effectiveness. She suggests educational initiatives and ‘roadshows’ to bridge the knowledge gap, enabling business teams to understand the potential of AI solutions and contribute valuable insights. Regan highlights a decision mapping approach to identify key decisions that can be supported by AI, encouraging a collaborative environment for idea generation and prioritization. “Have some sort of process for them to know who you are, understand how you can support them... having somebody who will spend some time with those folks to understand deeper,” she advises. This collaborative approach not only aids in identifying viable AI use cases but also ensures that AI solutions are aligned with business needs and objectives.

Rehgan Avon Headshot
Rehgan Avon

Co-founder & CEO at AlignAI

View More Webinars

Related

webinar

Building an AI Strategy: Key Steps for Aligning AI with Business Goals

Experts unpack the key steps necessary for building a comprehensive AI strategy that resonates with your organization's objectives.

webinar

Building Trust in AI: Scaling Responsible AI Within Your Organization

Explore actionable strategies for embedding responsible AI principles across your organization's AI initiatives.

webinar

Getting ROI from AI

In this webinar, Cal shares lessons learned from real-world examples about how to safely implement AI in your organization.

webinar

Leading with AI: Leadership Insights on Driving Successful AI Transformation

C-level leaders from industry and government will explore how they're harnessing AI to propel their organizations forward.

webinar

From Learning to Earning: Navigating the AI Job Landscape

Dmitry Shapiro, CEO at MindStudio.ai, Alex Jaimes, Chief AI Officer at Dataminr, and Caryn Tan, Learning Solutions Architect at DataCamp, will guide you through the evolving landscape of AI careers.

webinar

Charting the Path: What the Future Holds for Generative AI

Explore how generative AI tools & technologies will evolve in the months and years to come and navigate through emerging trends, potential breakthrough applications, and the strategic implications for business.

Hands-on learning experience

Companies using DataCamp achieve course completion rates 6X higher than traditional online course providers

Learn More

Upskill your teams in data science and analytics

Learn More

Join 5,000+ companies and 80% of the Fortune 1000 who use DataCamp to upskill their teams.

Don’t just take our word for it.