How many ideas have you heard for how your company can use AI?
Tech leaders are currently dealing with a surge of AI ideas and demand. Leadership wants to implement AI immediately, companies are flooded with outreach from countless AI vendors, and everyone in the organization has ideas for the best way to utilize AI. That’s why 97% say the urgency to deploy AI has increased within their company in the past six months.
How can you organize enterprise AI ideation and brainstorming and create a structured approach that transforms this noise into actionable, high-value ideas aligned with strategic business objectives?
Enterprise AI Ideation Challenges
Enterprises are under incredible pressure (from inside and outside the organization) to prioritize AI transformation. Enterprises are receiving a high volume of proposals from AI vendors for countless different use cases.
Shadow AI increases the pressure as employees are already using AI without the company’s knowledge. Zendesk research shows almost 50% of customer service agents are using unsanctioned AI tools. This creates security risks and a scattered AI transformation.
It’s clear many organizations are struggling with a lack of a centralized AI transformation strategy. Too many voices are presenting too many ideas without clear priorities or a consistent framework. The lack of a central repository for these ideas results in duplicated efforts and lost insights. Many enterprises also lack one person who has taken clear ownership of the organization’s AI strategy.
Meanwhile, 61% of tech leaders anticipate having just one year or less to implement their AI strategy before incurring significant negative business impacts from falling behind (according to Cisco research conducted a year and a half ago…). How can your enterprise cut through the noise?
Organizing the Enterprise AI Ideation Process
The first step in creating your enterprise AI strategy is to organize a process for brainstorming and organizing potential AI development projects.
Establish Cross-Functional Ideation Teams
Bring together key stakeholders, including product owners, IT leaders, data scientists, customer support, finance, and marketing. This provides a range of perspectives to help understand all the problems and opportunities AI could address. This ensures AI ideas are aligned with enterprise objectives and not siloed within a single department.
When it comes time to implement AI projects, you’ll encounter less resistance to adoption by involving more stakeholders in the process who are more likely to champion the implementation.
Implement Structured Brainstorming Sessions
Most enterprises have an unstructured approach to AI brainstorming. Letting enterprise AI ideation occur organically across Slack channels, internal emails, and impromptu conversations leads these ideas to be forgotten, duplicated, or disconnected from broader strategic goals.
Instead, schedule regular ideation workshops with clear agendas and objectives. Provide prompts to guide thinking, such as “What are the most repetitive tasks on your team?” or “Where are delays or inefficiencies costing the most time or money?” Encourage team members to think about outcomes, not just tools.
By making enterprise AI ideation a recurring, visible, and structured activity, you elevate it from passive to proactive. Teams will come to these sessions prepared, and over time, you’ll create a reliable pipeline of thoughtful, impactful AI opportunities that can be prioritized and acted upon.
Create Visibility and Organization
When teams don’t know what’s already been proposed or what’s currently being worked on, they may waste time duplicating efforts or miss out on potentially impactful AI transformations. That’s why visibility is a key part of streamlining the enterprise AI ideation process.
Start by creating a centralized, accessible system for documenting and tracking ideas. The results of your brainstorming sessions should be added to this system and made accessible company-wide.
Organizing your enterprise AI ideation and brainstorming and making it visible to everyone in the enterprise helps build trust, increase collaboration, and generate momentum for your enterprise AI transformation.
This level of transparency also helps with AI adoption. Gigster’s research into 6 change management strategies to avoid enterprise AI adoption pitfalls found that 39% of employees say that a lack of awareness around the reason for change would make them most resistant to that change.
Is your organization ready for AI?
Set Clear Guidelines and Evaluation Criteria
As you collect ideas for enterprise AI transformations, you need to set clear guidelines for how you will evaluate and prioritize AI opportunities. These evaluation criteria are especially important to weigh against the bias of stakeholders who will all have a project in which they are more invested.
Multinational fashion retailer, H&M, conducted a thorough evaluation of potential AI algorithms before implementing their AI strategy. The company faced challenges with inventory management, pricing optimization, and predicting rapidly changing fashion trends. With how quickly the fashion industry moves, traditional inventory and pricing management wasn’t effective enough.
H&M’s team of data scientists tested three different approaches to using AI for pricing optimization. They tested pure employee pricing, AI algorithm-only pricing, and a hybrid model where AI-generated recommendations were reviewed and adjusted by employees. The hybrid model proved most effective. It was implemented enterprise-wide and now allows H&M to customize store inventory and pricing based on a wider variety of factors and improve overall operational efficiency.
When setting your own evaluation criteria, focus on:
- Potential ROI: Will this project save time, reduce cost, or improve customer satisfaction?
- Alignment with business objectives: Does it help the company achieve its top priorities?
- Feasibility: Is the data needed readily available? Can this AI project be implemented with available talent and tools?
- Risk: How likely is this project to reach completion and deliver on its promised results?
How Enterprise AI Ideation Fits Into Your AI Journey
Organizing your enterprise AI ideation is not the end, it's the beginning. This stage helps enterprises move from abstract excitement about AI to a focused pipeline of vetted use cases. Once ideas are collected and prioritized, you can begin assessing build-or-buy decisions, selecting technology partners, allocating budgets, and launching pilot projects.
If your organization is struggling to prioritize AI opportunities or is unsure how to manage the flood of ideas and vendor outreach, our AI Strategy Workshop is the next step. Contact us today to reserve your spot in the workshop.
