
Published by Vedant Sharma in Additional Blogs
In 2024, JLL, a global real estate services firm, transformed a partnership agreement process that previously took up to two months into a task completed in under five hours using their tailored AI model, JLL GPT.
This significant improvement showcases AI's potential to streamline complex workflows, enhance efficiency, and reduce operational timelines.
By integrating AI into their processes, JLL not only accelerated their operations but also empowered over 400 marketing team members to become AI innovators, leveraging multiple AI tools daily to optimize their work.
This guide explores how to use AI to increase productivity with practical, actionable methods that transform workflows and drive meaningful results.
How AI Bridges the Gap Between Effort and Efficiency
The gap between effort and meaningful outcomes often stems from the repetitive, manual processes that dominate daily workflows. AI is transforming this dynamic by acting as a connector—bridging raw human effort with efficient, outcome-driven systems.

Source: Here is a LinkedIn Post by Manish Sharma, Chairman of Panasonic, describing how AI works on innovation and development to bridge the gap between effort and growth.
At its core, AI identifies inefficiencies in routine tasks and builds faster and more accurate solutions. Consider financial reconciliation. Previously, employees would spend hours cross-referencing spreadsheets. AI automates these processes, and anomalies are flagged in seconds.
Let's begin with an example. A logistics company, UPS, uses AI to optimize delivery routes. Their ORION AI system analyzes real-time traffic patterns, weather data, and package volumes to create the most efficient delivery routes.
This innovation has saved the company 100 million miles annually, reducing costs and enhancing driver productivity.
Now, let’s see how this begins with transforming manual tasks into automated, streamlined workflows.
1. From Manual to Automated
Every workplace has repetitive tasks—data entry, scheduling, or inventory checks. AI simplifies these through workflow automation, ensuring accuracy and saving time. Consulting firms in Australia, such as Grant Thornton and EY, have implemented AI tools to automate tasks like email drafting and data formatting, saving employees up to 7.5 hours per week.
Methods include:
- Process Mapping: Identifying workflows that can be streamlined with AI-powered automation.
- Trigger-Based Actions: AI automates tasks based on predefined triggers, like processing emails into tasks.
- Robotic Process Automation (RPA): AI-driven bots handle tasks like data entry and invoice processing.
- Intelligent Document Processing: AI extracts and processes information from documents, streamlining workflows.
Organizations using AI for content creation have seen a 60% increase in productivity and a 30% improvement in content quality.
With routine tasks under control, the next challenge is making decisions faster without sacrificing quality.
2. From Information Overload to Insightful Decisions
AI turns mountains of data into clear, actionable insights. It doesn’t just process information; it makes it useful. Researchers at a materials science lab using AI discovered 44% more materials and increased patent filings by 39%, accelerating innovation.
Key methods include:
- Real-Time Dashboards: AI delivers live updates on performance metrics, making it easier to pivot strategies.
- Predictive Analytics: AI forecasts future trends based on historical data, aiding in resource allocation and market strategy.
- Natural Language Processing (NLP): AI interprets and summarizes complex information, making data more accessible.
Companies that integrate AI analytics report 25% faster decision-making cycles. This could result in gen AI tools to a 0.1% to 0.6% yearly increase in labor productivity through 2040.
While decisions are faster, AI also enables better collaboration, ensuring everyone on the team stays aligned.
3. From Fragmented Collaboration to Unified Workflows
AI strengthens teamwork by bridging gaps in communication and organization. Zaha Hadid Architects uses generative AI tools to produce intricate designs more efficiently, effectively doubling or tripling productivity in project competition stages.
These methods stand out:
- AI-Driven Collaboration Platforms: These are tools that integrate AI to manage projects, assign tasks, and monitor progress. Tools like Microsoft 365 use AI to suggest action items from meetings.
- Language Processing: Breaks down language barriers with real-time translation or sentiment analysis, facilitating global teamwork.
Businesses using AI collaboration tools report a 15% increase in productivity due to reduced communication delays.
Once collaboration improves, creativity thrives, especially when AI supports rather than replaces the creative process.
4. From Creative Block to Continuous Innovation
AI complements human creativity by handling repetitive tasks or generating fresh ideas. Content creators are leveraging AI tools like Synthesia to produce lifelike AI video versions of themselves, reducing production times and costs and enabling earnings up to $60,000 a month.
Professionals focus on innovation through methods like:
- Pattern Recognition: AI identifies trends in design, writing, or product development to inspire new approaches.
- Iterative Feedback: AI provides immediate feedback on drafts, designs, or concepts, speeding up revisions.
- Generative Design: AI creates multiple design options based on specific parameters, inspiring new solutions.
- Content Generation: AI assists in drafting articles, creating visuals, and composing music, expediting the creative process.
AI-generated design variations helped Coca-Cola cut creative development time by 30%.
Creativity aside, AI also manages complex operations behind the scenes, ensuring workflows run smoothly.
5. From Reactive to Proactive Management
AI helps organizations move from reacting to problems to proactively addressing them. Companies like FedEx and Nestle utilize AI for intelligent logistics management, reducing operational downtime by 20%.

Methods include:
- Anomaly Detection: AI spots irregularities in processes or performance, alerting teams before issues escalate.
- Dynamic Scheduling: AI adjusts project timelines or resource allocation in real-time based on current data.
- Predictive Maintenance: AI forecasts equipment failures, allowing for scheduled maintenance and reduced downtime.
These innovations are just the beginning—emerging trends like Agentic AI are poised to take productivity to the next level.
6. From Busy to Balanced
AI isn’t just for businesses—it’s a powerful personal assistant. Employees using personal AI tools report a 12% increase in task completion rates, according to Inc.
Methods include:
- AI-Powered Time Management: AI prioritizes tasks based on deadlines, importance, and personal work patterns. Tools like RescueTime provide actionable insights into how time is spent and suggest improvements.
- Focus Enhancement: AI identifies productivity patterns and recommends optimal working hours or break schedules.
7. Agentic AI: Redefining Autonomy in Work
Agentic AI represents a significant advancement in artificial intelligence, moving beyond simple task automation to systems capable of autonomous decision-making and action.
It is said that by 2026, over 80% of enterprises will use AI agents and agentic workflows for data management. This emerging field combines adaptability with decision-making, promising breakthroughs in productivity.
Key Applications:
- Self-Managing Teams: Agentic AI can independently analyze challenges, develop strategies, and execute tasks, making it a transformative force in enhancing productivity across various industries.
- Real-Time Problem Solving: Agentic AI employs sophisticated reasoning and iterative planning to address complex, multi-step problems. This makes it suitable for tasks such as supply chain optimization and cybersecurity vulnerability analysis.
Ema is a universal AI employee powered by advanced Agentic AI, designed to enhance productivity across various enterprise roles. With its Generative Workflow Engine™ and EmaFusion™ technology, Ema can autonomously execute complex workflows, learn from human feedback, and integrate seamlessly with existing systems.
For example, Envoy Global, a leader in immigration solutions, serves over 1,500 companies worldwide. Facing thousands of critical requests annually, Envoy needed a scalable solution to maintain fast, accurate responses while growing its operations.

When in-house AI efforts fell short, Envoy turned to Ema’s Universal AI Employee. Ema’s Customer Support Assistant AI Employee automated over 50% of support tickets, saving 70%-80% of team time.
Additionally, Envoy’s affiliated law firm used Ema's Legal Compliance AI Employee to accelerate legal research and document review, significantly improving client satisfaction.
AI’s value lies in its seamless integration into both personal and professional spaces, but success depends on strategic implementation.
Building a Long-Term AI Strategy

To maximize AI's impact, organizations and individuals must treat it as more than a tool. According to Boston Consulting, companies that adopt AI with clear strategies achieve 30% higher ROI on their implementations.
It’s a long-term investment requiring:
1. Identifying AI-Ready Tasks
Start with workflows that can deliver immediate value through automation or analysis. Tasks such as repetitive data entry, customer support, or logistics optimization are ideal.
Mapping bottlenecks and aligning AI tools to solve these issues ensures a strong foundation for success.
2. Continuous Learning and Adaptation
AI tools evolve rapidly, and teams need to stay updated. Providing regular training helps employees leverage AI effectively and fosters innovation.
This approach also minimizes resistance to change and encourages creative applications of AI in different workflows.
3. Evaluating AI’s Impact Regularly
AI implementations require ongoing evaluation. Regularly track performance metrics, such as time savings, error reduction, or improved customer satisfaction.
Use this feedback to optimize processes or pivot strategies if necessary.
4. Scaling AI Across Functions
Once AI proves its effectiveness in specific areas, scale it to other functions. Tools that integrate seamlessly with your infrastructure and workflows can multiply productivity gains across departments.
A clear, long-term strategy ensures AI drives sustained productivity gains, supports organizational growth, and adapts to evolving business needs in the future.
Turning Potential into Productivity
The true potential of AI lies in its ability to bridge human ingenuity with technological efficiency. From solving repetitive challenges to enabling autonomous decision-making, AI tools are rewriting the rules of productivity. As businesses adopt these innovations, the focus shifts from merely keeping up to driving meaningful, scalable progress.
AI tools, especially advancements like Agentic AI, are paving the way for intelligent, adaptable systems that elevate efficiency while empowering human creativity. Businesses that embrace this evolution today will lead tomorrow’s innovation.
If you’re ready to explore how AI can revolutionize your operations, from automating workflows to delivering faster, smarter solutions, discover the possibilities with Ema’s Universal AI Employee. Hire Ema today!