In less than a decade, Artificial Intelligence (AI) has evolved from a tech buzzword to a transformative force, not just for organizations but the world as a whole.
Companies and organizations served as the perfect microcosms for testing the capabilities and impact of AI tools in several areas, including productivity.
Let’s take a look at some of the ways AI enhances a company’s productivity. That includes both employee and output (service and products) productivity.
Automation
It’s worth noting that automation predates AI, but there is no denying that AI has made automation more accessible and widespread.
With the right tools, almost all companies and organizations can automate at least some of their most repetitive tasks, with some degree of human intervention (if necessary).
This includes administrative tasks like handling employee requests or client-facing tasks like sorting and prioritizing complaints.
AI-augmented automation is not limited to the digital elements of a business; several manufacturing companies’ processes can also be automated to enhance productivity.
Supporting Internal and External Communication
AI can help streamline a wide range of internal and external communications.
Whether it’s employees writing emails to their managers, preparing reports for their supervisors, or chatbots that allow companies to automate a significant segment of all client communication or chats, AI can make companies significantly more productive.
An average employee spends about 28% of their time writing or reading emails at work, and at least the writing process and time can be cut down significantly with generative AI tools like ChatGPT.
The same applies to cold communication with external stakeholders, like promotional emails and social media posts. Chatbots can help a relatively small team of human professionals handle the massive influx of messages from customers since, with enough training, most customer queries can be answered and resolved on the AI level.
Culture of Self-Learning
AI tools can also help companies cut short the time spent on training and guiding their employees. With the right guidelines and promoting a culture of self-learning, employees can learn several elements of their jobs using AI tools at their own pace.
This saves both their time and the time of the peers or supervisors they would have turned to for help or learning, increasing the productivity of the entire team. AI tools can also help employees learn skills and tricks that can make them more productive.
Role-Expansion
AI tools can help an employee significantly enhance their skill set and, with some time and effort, perform tasks they are not specifically trained to do.
This includes business graduates writing queries for databases (which falls under programming) or engineers developing business reports instead of carting the task off to another team.
This can significantly increase the productivity of individuals and teams and, by extension, the company. Cross-skill development can also make workforces more resilient.
Data-Driven Process Efficiency
In office, industrial, service, and several other settings, AI and Machine Learning (ML) algorithms can be trained to identify the best, most optimal processes if they have enough data points.
These algorithms can identify patterns and come up with configurations that conventional wisdom and calculations are simply not equipped for.
Process efficiencies like pairing certain doctors with certain nurses and anesthesiologists in an operation theater or shortening the route forklifts have to take within a warehouse by rearranging the shelves can yield enormous productivity gains and more efficient use of resources.
AI tools and the data they help you process (to generate useful insights) can also help businesses make optimal choices, whether it’s for third-party vendors or finding the right tool, like choosing the best VPN services.
Predictive Analytics
Lastly, the right AI tools and good data collection and processing practices can help companies predict certain outcomes and challenges, which may lead to predictive decision-making.
For example, companies may identify that they are short-staffed on certain days or when certain conditions are met and plan their staffing accordingly.
An organization may discover patterns in its supply chain delays that encourage it to change schedules or vendors to ensure timely deliveries.
Conclusion
AI can help individuals, teams, and, by extension, entire companies become more productive in several ways. The primary role an AI can play in the productivity of a company is removing any inefficiencies.
However, it’s important to understand the vulnerabilities and limitations of AI as well as to ensure that AI tools remain an asset for a company’s productivity and do not become a liability.
