Author: IRPA AI Senior Analyst, Kieran Gilmurray
What if your new hire could analyse a million data points before you’ve finished your morning coffee? This isn’t a far off future scenario; it’s an immediate strategic opportunity.
Leading analysts estimate that AI, including nongenerative artificial intelligence and analytics, could unlock 15% to 40% of economic value. For leaders, capturing that initial 15% productivity gain is the new benchmark for survival.
This is about harnessing digital co-workers, such as AI agents, RPA bots, and intelligent automation, as core members of your team. The question is not if, but how you will manage digital workers to drive measurable business impact. This is, or must be, a top-down imperative.
The 15% Breakdown: Efficiency, Augmentation, Innovation
Where does this 15% gain actually come from? It’s not a single lever; it’s a combination of three distinct advantages.
First, radical efficiency. Automation can slash task times by up to 70% in areas such as data entry or invoice processing. For example, when a global insurer deployed AI for claims, it was able to handle 1.2 million requests annually, 24/7. This surgically removed low-value work to free talent for more strategic, value adding work.
Next, intelligent augmentation. Augmentation is about helping your experts work faster and smarter. For example, in finance, AI algorithms now support wealth managers in analysing market data in real-time, markedly improving the accuracy of their recommendations and helping their clients’ financial position. AI doesn’t replace the expert it augments the team.
Finally, scaled innovation. Digital workers unlock business models that were previously thought impossible. For example, Klarna’s AI assistant now handles a volume of customer chats equivalent to the work of 700 full-time agents. This allows them to deliver elite 24/7 service and expand into global markets without a proportional increase in headcount and expense.
Why Haven’t Businesses Achieved Operational Efficiencies?
The biggest barrier to new efficiencies is organisational drag. Organisational drag actively erodes ROI. Poorly integrated AI creates ‘shadow work’ as teams are forced to constantly fix errors and complete inefficient and complex workarounds, with ever-increasing amounts of manual, robotic work consuming workers’ days. In addition, critical IT skill gaps can delay the deployment of AI by 12-18 months, further reducing businesses’ ability to leverage AI and create value.
How does organisational drag show up?
- Cultural Inertia: The seven most expensive words in business: “We have always done it this way.”
- Managerial Blind Spots: Leaders are often unprepared to manage a hybrid team that combines humans and AI.
- Skills Mismatch: A vast gap between the AI tools you have and the skills your workforce needs to use them effectively, resulting in delays, reduced customer satisfaction, and revenue losses
And it’s all underpinned by employee who are nervous about losing their jobs to digital work.
However, automation isn’t about replacement but redistribution. Digital workers should be tasked with handling repetitive work tasks, freeing them to focus on complex tasks that require human judgment, creativity, and intellectual growth.
So, what should CEOs do to leverage AI?
The CEO Playbook: Your 6-Step Action Plan
Are you ready to turn AI potential into AI performance?
While all five steps are critical, success hinges on sequencing.
CEOs must start with Step 1 (Tech Readiness), then move to Step 2 (Skills Upgrading), and only then proceed to Step 3 (Rules of Engagement) and so on – in order to build a solid foundation for AI, avoiding ‘pilot purgatory’.
Step 1: Get Your Tech “Agent Ready”.
Assess your current tech stack to integrate AI with minimal friction. Your goal: pilot a single workflow in under 90 days (like automated invoice processing) to demonstrate immediate ROI and build momentum.
Step 2: Launch Targeted Upskilling.
Ditch generic training. Teach specific human-AI collaboration skills, including data interpretation, bot oversight, and workflow design. Focus = speed.
Step 3: Establish Rules of Engagement.
You wouldn’t hire a person without a job description; do the same for bots. Define their tasks, KPIs, and owners.
Clarity creates trust.
Step 4: Champion a Culture of Experimentation.
Not every pilot will be a home run. Create an environment that promotes safe experimentation and psychological safety, enabling your teams to experiment, fail quickly, and learn from their mistakes.
Reward the effort, not just the outcome.
Step 5: Communicate the Opportunity.
Frame digital co-workers as an opportunity for more interesting and valuable work, rather than a threat. Remember that new hire analysing data by coffee time? With your tech ready and rules defined, they’re ready to start next quarter.
Step 6: Track and Communicate The Results
To demonstrate that digital workers are making a positive impact, track specific metrics, such as bot accuracy rates, process cycle times, or employee Net Promoter Score (eNPS), to gauge and communicate their positive effect on your team and business.
From Insight to Impact
The integration of digital co-workers into workplaces is a defining leadership challenge. The stakes are clear: research shows early AI adopters can achieve significantly faster revenue growth than laggards.
This isn’t just about staying competitive; it’s about leading the pack. Your 15% gain starts with one process, one pilot, one quarter.
The only question left is: What will you automate first?
About the Author: Kieran Gilmurray
Senior IRPA AI Analyst & Advisor, Kieran Gilmurray is a certified executive coach, intelligent automation & digital transformation thought leader & content guru focused on helping solve complicated problems others can't. For the past 25+ years, he has driven business digital transformation programs across a range of industries like digital technologies, intelligent automation, data analytics, social media and robotic process automation, having generated millions of dollars of value.
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Originally posted on 2025-01-28 in the IRPA AI Network — Announcements & Updates