Artificial intelligence-powered tools are positively impacting job creation, and this sector of tech is still in its infancy. With AI at the forefront, the future of work is shifting into a support automation movement, says David Karandish, CEO, Capacity.
It’s not out of the ordinary to be weary when imagining the future of work, paired with artificial intelligence (AI) and machine learning (ML), as a death sentence to the typical 9-5 job. However, AI and ML technologies will create 58 millionOpens a new window more jobs than they displace, so the narrative itself is in dire need of a shift. AI will also lead to higher spending and more investment for those who enable the services. Long term, the influx in AI and ML in automation will lead to more employment opportunities.Â
As a result, the types of jobs available in the future will change. Each AI system must be designed specifically for a certain job or task, potentially making jobs with those particular skills less available while also creating jobs for AI programmers.
With a new outlook and understanding of AI’s impact on the future of work and automation, teams are boosting productivity with intelligent tools and creating more time for high-ROI activities. In fact, the AI software industry is expected to hit half a trillion dollarsOpens a new window by 2024.
To make a successful transition into the future of AI and ML, we must shift the dialogue and focus on how technology is helping teams prosper.Â
AI is changing the future of work in three fundamental ways:Â
1. Increased Collaboration and Productivity
Collaboration and productivity are a driving force for a successful workplace environment. Gartner predicts Opens a new window 70% of organizations leveraging collaborative work management systems will see significant performance improvements with their teams by 2022. It’s clear by harmonizing the team’s talents with AI tools, productivity can prosper and make collaboration easier, faster, and more effective.Â
Expert finder toolsOpens a new window are a key example of how AI uses collaboration to help businesses drive productivity. Created to cut the hassle of searching for complex answers, expert finder software identifies internal subject matter experts (SMEs) and enables the use of existing knowledge on a platform.Â
Similarly, AI-powered chatbots and helpdesks also influence productivity and collaboration efforts by SMEs via a chat portal. Inquiries asking in-depth questions are delivered to the expert of choice. With AI, replies from SMEs are automatically added to your organization’s knowledge base, ensuring all future questions get the same helpful answer.Â
2. Intelligence-Driven Knowledge
The â€œknowledge is powerâ€ line is outdated. In the future of work, knowledge is profits. By centralizing organizational data, tacit knowledge and answers to FAQs, organizations are saving millions. According to GartnerOpens a new window , poor data costs businesses upward of $15 million annually.Â
Knowledge bases and support automation tools, including robotic process automationOpens a new window (RPA), can automate repetitive tasks, giving teams more time for high-ROI activities. In short, cloud drives are pushing offline activities online and expediting workflows without human intervention. While cloud storage remains valuable, searchable documents, extensible permissions structures and workflow automations are enabling teams to crush key performance indicators like never before.Â
With AI at the forefront of the future of work, siloed data and knowledge is a notion of the past. Support automation technologies can mine for data through a company’s customer management platform, enterprise planning tools, marketing automation software and more.
3. AI-Powered Assistants
One of the best reasons to anticipate the future of work is the increase of digital assistants. Although chatbots are nothing too futuristic, deploying them from the top-down enhances productivity. Older, rule-based bots have a narrower scope of function, but with AI and ML, these bots are unlocking the true potential of digital assistants.
Most bot solutions are armed with natural language processing (NLP) for clear support. The goal of NLP is to read, decipher, understand and make sense of human languages in a valuable manner. No matter how something is phrased, NLP can understand the question and provide answers with a high level of accuracy.Â
Yet, if you’re still on the fence about AI, human-in-the-loop (HITL) tech should mitigate concerns. Combining the expertise of dedicated teammates with a preexisting knowledge base can result in a high-performing information-sharing platform. For example, if the intelligent chatbot is unsure how to respond to a query, the message is instantly forwarded to a subject matter expert. After a reply is received, ML updates the chatbot’s knowledge base, guaranteeing the same response for future inquiries.Â
AI-powered tools are revolutionizing the workplace, and it’s only the beginning of a support automation movement. With increased collaboration, intelligence-driven knowledge, and AI-powered assistants, the future of work will provide employees more time to focus on the value-added work that inspires and motivates them each day.Â