in February, the Business Agility Institute released an interesting report named “From Constraints to Capabilities AI as a Force Multiplier”. It’s definitely worth reading. Two things we loved the most: 1. it gives actual numbers of force multiplier for different organizational dimensions and 2. it highlights that AI brought as it is in organizations can make things worse…
Many view Artificial Intelligence as a tool that can make businesses faster, smarter, and more efficient. That’s great, but what if, instead of helping, AI actually makes things worse?
This could result when organizations struggling with slow decision-making, rigid processes, or poor-quality data, introduce AI. Instead of improving performance, AI can magnify existing problems.
A recent study from Business Agility Institute shows that AI can act as a force multiplier, meaning it can drastically increase the impact of business processes, improve operations and customer engagement. But this only works if the company is ready-to-use AI effectively. Otherwise, AI won’t fix problems—it will make them worse.
AI as a Force Multiplier: The Potential
The research highlights that AI can enhance many business areas, including:
- Product development: AI is able to speed up time-to-market (1.4X to 2.7X)
- Decision-making: AI insights help leaders make better choices faster /1.3X to 3.0X)
- Operational efficiency: AI has the potential to reduce costs and automate repetitive tasks (1.2X to 2.5)
- Customer experience: AI personalizes interactions and ensures enhanced service availability (1.4X to .7X)
However, the study also warns that AI’s impact depends on the organization’s ability to act on it. If leaders and teams can’t move fast, then AI benefits disappear.
The Reality: AI Can Make Things Worse
Imagine this: Your AI system generates insights three times faster, but management still takes weeks to decide. Or AI improves workflow efficiency, but rigid approval processes and unnecessary meetings delay implementation. Instead of solving problems, AI exposes and worsens them—making bottlenecks more visible but not fixing them.
This happens because AI operates within an existing system, and if that system is already slow, bureaucratic, or fragmented, AI won’t change that—it will magnify the dysfunction. If decision-makers hesitate, if teams work in silos, or if bad data feeds AI models, the outcome will be more confusion, not more efficiency. AI doesn’t create agility; it requires it.
Disappointment awaits leaders who expect AI to “magically” solve problems without first addressing structural inefficiencies.
If your company struggles with slow decision-making, unclear priorities, or outdated workflows, AI will only highlight these weaknesses more painfully. Without streamlined processes, clear accountability, and empowered teams, AI becomes just another expensive tool that cannot deliver its promised value.
Breaking Free: How to Avoid AI Failure
To make AI work, organizations must first remove the barriers that slow them down. Some key areas need your attention:
- Faster Decision-Making: AI works best when leaders can act quickly on its insights.
- Reduce unnecessary approvals and bureaucracy by adopting decentralized decision-making models such as those used in Agile organizations.
- Empower cross-functional teams to make autonomous, AI-driven decisions without waiting for hierarchical approvals.
- Enable Adaptive Strategy and Dynamic Funding Models: Traditional budgeting slows down AI adoption.
- Use Objectives and Key Results (OKRs) to ensure AI investments are outcome-driven and directly linked to business goals.
- Lean Portfolio Management helps organizations assess and manage demand in a lean and structured way, ensuring that funding decisions align with real-time priorities. By supporting iterative and incremental work, it enables a shift towards flexible budgeting based on actual measurable value, rather than rigid annual planning cycles.
- Adopt flexible budgeting approaches that enable teams to reallocate resources quickly based on AI-driven insights.
- Optimized Workflows: AI thrives in streamlined, agile environments.
- Identify and remove bottlenecks in processes and team collaboration using Value Stream Mapping, a key tool for visualizing workflows, pinpointing inefficiencies, and optimizing the end-to-end flow of work.
- Ensure AI-driven insights can be used without unnecessary delays.
The Key Takeaway: AI Won’t Fix a Broken System
AI is a powerful tool, but it can’t fix bad processes, slow leadership, or rigid company structures.
Organizations that benefit from AI are the ones that:
- Fix internal inefficiencies first.
- Train employees to work with AI effectively.
- Make fast, data-driven decisions.
Prepare your organization for AI by embracing Business Agility, and it can become a true force multiplier for success.
Content: Human-Generated + AI Processing
