How to balance innovation with operational demands, and what responsible AI adoption looks like across the enterprise

Whether your organization is already deep into AI initiatives or just beginning to explore the possibilities, one thing is clear: artificial intelligence is fundamentally changing how leaders approach priorities, planning, and team collaboration.

In this insightful episode of Amplify Agile presented by Apptio an IBM company, Chris Ruch, CEO of Agile Rising, joins host Tracy Yen, to delve into the profound ways this shift is reshaping not only technology teams but also the very fabric of how organizations make decisions, allocate resources, and strategize for the future.

Tune in as Chris explores:

• The key challenges and significant shifts compelling organizations to re-evaluate their investment priorities, governance models, and overall operating models in this new era of AI.
• Actionable, practical steps your organization can take now to prepare its data infrastructure, establish robust governance frameworks, and adapt decision-making structures for an AI-driven landscape.
• Essential tools and agile practices that will help your teams stay aligned, effectively manage evolving priorities, and navigate the increasing complexities introduced by AI.
• Compelling real-world examples showcasing how forward-thinking organizations are successfully adapting their strategies to embrace and support impactful AI initiatives.

Don’t miss this crucial conversation on how AI is intertwined with the future of agile! Watch or Listen Here.

Read Transcript:

0:10 Welcome back to Amplify Agile, where we redefine agility by focusing on the crucial link between strategy and execution. I’m your host, Tracy, and today we’re diving into a topic dominating boardrooms and backlogs alike: Artificial Intelligence.

0:27 Whether companies are actively investing in AI or just beginning to explore its vast potential, it’s undeniably reshaping how leaders approach priorities, planning, and team collaboration. We’ll unpack the profound implications of this shift, not just for tech teams, but for how entire organizations make decisions, allocate resources, and prepare for the future.

0:48 Joining us today to break down what organizations should be doing now to get ready is Chris Ruch, CEO of Agile Rising. We’ll explore everything from organizing data and enhancing decision-making to establishing the necessary oversight as organizations venture into the world of AI. Our conversation will also cover how to strike a balance between innovation and operational needs, and what responsible AI adoption looks like across portfolios.

1:14 Chris, welcome to Amplify Agile! Could you please share a quick introduction of yourself?

1:19 Thanks, Tracy. It’s great to be here. As you mentioned, my name is Chris Ruch, and I’m the CEO of Agile Rising. Agile Rising helps organizations adopt new ways of working and discover the optimal path to deliver valuable products effectively.

1:38 My background is rooted in technology and software development, which evolved into organizational leadership, management, and strategic planning. AI, in many ways, brings together the core areas I’ve dedicated my career to and have helped other organizations navigate.

2:00 Awesome, thanks for that introduction, Chris. So, let’s get straight to it. What key challenges or shifts are you currently observing that are compelling organizations to fundamentally rethink their investment priorities, governance frameworks, and operating models in the context of AI?

2:19 Sure. It feels like everything revolves around AI these days. While some of this is driven by excitement and hype, the reality is that AI is prompting leaders to seriously consider the future trajectory of their organizations and their products.

2:38 The significant investment required for a technological transformation of AI’s scale is truly driving organizations to re-evaluate their overarching strategy and the prioritization of their future investments.

2:59 It’s definitely a substantial undertaking. For those just beginning to think about AI strategically, what initial steps can they take to prepare their data governance and decision-making structures? And what potential gains and benefits can organizations anticipate from this preparation?

3:17 I think the crucial element here is the strategic lens through which organizations approach AI. It’s not simply about implementing a new tool or platform and then proceeding with business as usual.

3:33 AI represents the next generation of thinking about product development and the very nature of products themselves. It’s fundamentally changing our approach to things.

3:47 Organizations need to strategically define what this evolution looks like within their specific context and how it will impact their entire portfolio of work and products. It’s not solely an IT concern; it will touch every facet of the organization in some way.

4:16 Leaders must consider how AI integrates into their portfolio, influences their budget, and determine what aspects need centralized oversight (like enterprise-level licensing) versus what can be decentralized to best suit different parts of the organization and their unique solutions.

4:46 This is a significant topic, and intertwined with it are critical security and governance concerns that must be addressed at the enterprise level. Simultaneously, organizations need to maintain the agility required to move swiftly in today’s rapidly evolving landscape, which AI is only accelerating.

5:18 So, what does it truly mean to think about AI strategically? It necessitates an overarching plan for the acceptable use of AI within the organization. It requires a robust portfolio management approach to determine budget and effort allocation for AI initiatives. Crucially, this portfolio management and budgeting must be agile.

5:51 One of the defining characteristics of AI is its constant evolution. New approaches and diverse ways to leverage it within an organization emerge daily. Therefore, organizations must adopt an agile, lean mindset for making bets and running experiments. Some of these will undoubtedly yield significant benefits, while others may not align or prove effective.

6:30 Strategic thinking in this context involves having a strategic planning framework that empowers the organization to conduct these experiments and establish feedback loops. These loops will enable the organization to continue investing in successful initiatives and pivot away from or discontinue those that aren’t delivering value.

6:56 Absolutely, leaders will need to take a step back and consider the broader implications.

7:02 So, Chris, could you share any specific examples or case studies of organizations that are successfully adapting their investment strategies or operating models to better support their AI initiatives?

7:14 Yes, it’s fair to say that virtually every company is experimenting with AI in some form or another. However, we’re likely not at the stage of definitive “case studies” because most organizations are still in the midst of this journey, either in the early stages or actively implementing changes.

7:36 What we are observing is a widespread recognition that beyond strategic planning and investment, organizations are critically examining whether their existing teams and organizational structures are optimally aligned with the new demands of AI-related work.

8:05 We currently have several large clients undergoing significant pivots, reorganizing their agile teams or agile release trains to ensure they possess the necessary skills and structural alignment to tackle the new work. This includes evaluating AI platforms, integrating AI as new capabilities or features into existing products, and establishing robust governance frameworks.

8:40 The fascinating aspect of what we’re seeing is the active evaluation of new operating models and team structures specifically designed to support the novel ways of working that leaders are envisioning.

9:01 While I won’t share specific company names due to the proprietary nature of their next-generation product strategies, I can outline what we’re seeing and how we’re assisting organizations. This involves identifying the areas where AI can generate the most significant impact, pinpointing skill gaps within their current workforce compared to future needs, and establishing new organizational structures with an “AI-first” approach.

9:49 I anticipate this “AI-first” orientation, shifting from a previous “mobile-first” mindset for new product development, will become increasingly prevalent throughout the remainder of this year and into the next, influencing both product development and organizational structures.

10:19 Another key observation from our work with various companies is the rapid consideration of AI governance as they evaluate incorporating AI solutions into their operational fabric. This goes beyond individual usage of tools like ChatGPT to encompass how to ensure AI usage aligns with leadership’s business, ethical, legal, and security objectives.

10:59 The establishment of structures and tools that empower leaders to implement effective AI governance is often one of the initial and crucial steps organizations are taking.

11:13 Absolutely, we’re all navigating this together. It’s valuable that you’re in a position to witness and guide these diverse journeys.

11:23 With shifting priorities and increasing complexity, maintaining alignment across the organization is more challenging than ever. What tools or practices are proving effective in helping organizations stay aligned and manage these complexities effectively?

11:38 Yes, at its core, agility is about the capacity to respond effectively to new developments. What we’re seeing now is that a robust agile approach, one that enables the intake of new information and facilitates pivoting, is becoming increasingly critical. Having the right tooling in place to support this is essential.

12:06 At Agile Rising, we are strong advocates for Targetprocess as a lean portfolio management solution. It allows for the visualization of the backlog and the ability to rapidly re-prioritize initiatives. So, having Targetprocess as the central tool for capturing AI initiatives, prioritizing them, assessing their impact, and tracking who’s involved is proving invaluable.

12:46 We’re also witnessing significant interest, pilot programs, and broader rollouts of IBM Orchestrate as organizations begin to pivot towards generative AI. A crucial decision for organizations is whether to build their own AI infrastructure – developing their own language models and agents – or to leverage existing agents available in the market. A tool like Orchestrate serves as a fantastic collaboration platform, enabling organizations to capitalize on work already accomplished by others.

13:41 I’m genuinely excited about the future of IBM Targetprocess and its synergy with IBM’s other products. It’s a powerful combination.

13:52 And so, Chris, for our final question: if there’s one key action that leaders should prioritize starting today to prepare for AI-driven changes, what would that be?

14:02 That’s a tough one, as AI is evolving in so many directions. However, the single most critical factor for leaders to succeed with AI is establishing the right team and team structure. This team will be responsible for evaluating where AI can be best applied, assessing relevant tools, defining corporate governance and security frameworks, and ultimately making informed decisions about prioritizing the work.

14:42 While having the best portfolio management tools and upskilling teams in the relevant technologies and tools are crucial, I believe building that core, capable team is the most important initial step today.

14:57 Absolutely, “teamwork makes the dream work,” as they say.

15:02 And that concludes today’s episode of Amplify Agile. Thank you so much, Chris, for sharing your valuable insights and experiences with us today. It was a pleasure having you on the show, and we hope to welcome you back for another episode.