The roles of leaders are shifting to product owners and organizations from process-led to product-led
The key to success in an increasingly autonomous world won’t be the technology – but the design of a new operating model to unlock its real value. The goal of autonomous transformation isn’t to eliminate jobs or replace people with AI.
Instead, it’s about thinking critically and strategically about how we use AI to enhance workflows, allowing teams and leaders to work more independently and focus on creating new value.
In the next five years, most companies will start operating like software businesses; instead of managing processes, leaders in departments like marketing or innovation for example, will be responsible for AI-driven products that will automate and improve key workflows and let them operate more autonomously.
There’s a common misconception that only tech and software businesses can benefit from autonomous transformation, but that’s not true.
There are many great use cases for autonomous transformation in freight, manufacturing, energy, and agriculture. And while adoption speed will vary by industry and company, the impact will be significant across the board. Automating repetitive tasks frees up human talent to focus on creating competitive advantages and driving innovation.
Let’s dive into your future role as an AI product manager and what that means for the business.
Use case: Marketing
Let’s start by exploring an example of how AI can transform key, repeatable workflows in marketing, showcasing the potential impact on efficiency and innovation.
Customer Data Analysis: Instead of manually analyzing customer data with third-party tools, AI can automate data collection, assess data quality, analyze at scale, and generate real-time insights, allowing us to use that time saved to focus on building relationships with partners and clients.
Segmentation: Moving from manual segmentation to AI-driven hyper-segmentation that enables the creation of dozens of detailed personas and pattern identification, allowing us to better understand and connect with diverse audiences.
Campaign Generation: AI can automate the creation and deployment of 1000s of personalized campaigns per customer segment and test it on synthetic audiences, freeing up time for mentorship for your creative team.
When we combine these AI-driven workflows, marketing teams can significantly shift how they spend their time, leading to greater efficiency and innovation.
A different type of leader
Because of these new workflows, we’ll see a significant shift in how time is spent. This shift will impact company operating models, requiring leaders to transition into roles as product owners. They’ll need to adapt to new responsibilities and drive the integration of AI within their teams.
This shift means that leaders will take on roles as product owners of AI-driven engines. For example, a CMO could oversee a marketing engine that responds to customer sentiment and tests campaigns, while a Head of Supply Chain Management might manage an engine that forecasts demand and optimizes inventory. Similarly, a VP of Innovation could be the product owner of an exponential innovation engine that rapidly generates and prioritizes new product ideas in minutes instead of months.
So, will you need to become a Product Owner?
Whether you’re in sales at a construction company or HR at a manufacturing company, you’ll likely find yourself involved in software and products in the coming years.
- Does your business unit relies on resource-intensive, repeatable workflows?
- Are you responsible for creating a competitive advantage for your company?
- Does your role involve testing different hypotheses and trying to predict a future scenario? For instance, if you’re in a food and beverage company predicting what today’s 18-year-olds will be consuming in a few years, you might see your role shift toward product ownership.
If any of these scenarios apply to you, you could soon find yourself becoming a product owner.
It’s important to note that we’re focusing on the measurable, repeatable aspects of different workflows. There are many parts of our roles, such as mentorship, cultural leadership, and ethical reasoning, that these AI engines aren’t equipped to handle yet. With that said, let’s discuss how product management and decision-making can drive this transformation.
How product management will drive decision making
Imagine a scenario where your team is now AI native. You’ve evaluated your workflows, identified opportunities to enhance them with AI tools or an underlying AI product, and are now working exponentially faster, delivering more informed results.
Here are some of the responsibilities of the AI product owners:
Identify and prioritize needs and opportunities
Leaders in various departments will become product owners, focusing on identifying and prioritizing needs and opportunities. They’ll think about what their product needs to test, for example, a feature that identifies regulatory obstacles for new financial or FDA-regulated products.
Determine the feasibility, desirability and viability of products
The product owner will lead determining the feasibility, desirability and viability of the features that make it into their product. So what can be built with the resources and with the budget that you have available to you?
Choosing the right technology is becoming easier, with many firms available to build the right product for you. What will be critical is knowing the outcome you are looking to achieve, and choosing a technology that can achieve that without over or under-investing.
Oversee the inputs, outcomes, performance and management of AI-driven workflows
Product owners will oversee the performance and management of AI-driven workflows.
When you look at it this way, product management shares a lot with business management, making the transition smoother than it might seem. And teams that learn to use their AI-driven products to ideate, build, test, and adapt quickly will be best positioned to create value.
The competitive landscape will shift
With AI-powered workflows enhancing traditionally time-intensive processes, the size of your company will begin to mean less and less; relying on a large innovation team or extensive research resources is no longer a secure competitive advantage. Barriers to entry are lowered, and companies that don’t adopt a product-centric model risk disruption from competitors that can easily mimic their previous workflows. To stay competitive, companies need to focus on unique, hard-to-copy capabilities, instead of relying on throwing money at resources and scale. It’s essential to think strategically about how AI can create new value, not just make the process of generating existing value more efficient.
First-mover advantage is significant in this AI transition, and many large companies are already making the shift. Slower adopters risk being left behind, much like when digital advertising lowered entry barriers and quickly disrupted traditional advertising.
From process-led to product-led company
From time-intensive workflows to AI-driven engines. From traditional roles to product ownership roles. From comparative advantage guarded by scale to a need to develop hard-to-copy capabilities.
These shifts are changing operating models, and there’s a paradigm shift from a process led company to a product led company.
These are some of the behaviors of this new way of operating:
Exponential workflows
Resource-intensive processes will transition to automated workflows, freeing up time for developing unique, hard-to-copy capabilities. This shift allows human creativity and initiative to thrive, leveling the playing field in terms of processes and workflows.
Reduced dependency on large resource pools
Companies will adopt systems that can handle increased workloads without a proportional rise in resources. This means scaling operations exponentially, improving efficiency, and reducing the dependency on large resource pools.
Decentralized model
We’ll see a reduction in interdepartmental reliance, minimizing bottlenecks and delays. This decentralized approach focuses on real-time responsiveness and agile adaptability, enabling teams to operate more independently and efficiently.
When business functions become so independent, what connects them?
As business functions become more independent with autonomous transformation and rely less on other units or stakeholders, maintaining connectivity between different units is crucial. This relies on two key aspects: humans and technology. Humans bring company values, culture, and accountability into workflows, leading strategic objectives and making critical decisions. Technology, particularly data and APIs, ensures interoperability between departments. This way, business units can operate independently while sharing valuable insights, adding a new dimension of intellectual property to the company’s assets.
The challenges
What are some of the challenges with adopting this approach and the move towards an AI product-led operating model?
Assessing ROI at an operating model level: Individual business units are responsible for their AI product use cases, making it harder to assess the overall ROI at an operating model level.
Cultural adjustment: We’ll see a shift from data-driven to reason-driven decision-making, requiring significant cultural adjustment and change management.
Legacy tech and IT systems: Integrating AI with existing legacy technology and IT systems is a major consideration.
Data quality and governance: Ensuring high data quality and strong governance is critical for AI effectiveness.
Identifying a new competitive advantage: As the playing field levels with AI, companies must identify new competitive advantages beyond scale and traditional processes.
Macro impact of AI: Energy usage and bias reinforcement are broad challenges that shouldn’t be overlooked.
The future of organizations in an autonomous world
- The future operating model will be product-led, with AI-driven engines leading workflows.
- Roles will shift toward product ownership, but this doesn’t mean non-technical people need to become highly technical. It’s about adopting a product management approach to decision-making instead of a process management approach.
- As key workflows become commoditized, companies will need to develop new, hard-to-copy capabilities to maintain their competitive edge.
Want to discover how your business can capture the opportunity of AI? Let’s talk!
