In just a year, we heard a lot about Generative AI and its real impact on how we work today.

With ChatGPT bringing a massive transformation to the workplace with a new concept, Bring Your Own AI, industry leaders are expected to experience a paradigm shift in the workplace for AI.

The fundamental GenAI potential is creating a new wave of opportunities, which certainly change the world of work.

So, what will a workplace look like in the age of AI, and what do AI predictions for the Workplace mean for you?

Here are the top 10 workplace predictions in the age of AI for 2024. Let’s discover how AI predictions in the workplace can shape the future of work.

Natural language processing, or NLP, exhibits excellent proficiencies in human language understanding. Probably, it drives massive improvements in AI innovation and ultimately brings to the forefront a relatively advanced AI form—Generative AI.

With capabilities such as text generation, translation, language processing, and summarization, Generative AI gives a comprehensive makeover to chatbots and virtual agents.

Beyond typical yes or no answers, Generative AI-driven chatbots or virtual agents can solve problems for repetitive or critical queries.

Chatbot conversations can have more than predefined dialog flows. Its underlying technology, GenAI or LLM, can learn from user interactions and predict the following sequence of conversation flows, thus removing the bot training time and helping boost problem resolutions for companies with low efforts.

Similarly, virtual agents can take part in problem-solving for customer support services more efficiently, leaving less work for agents and freeing them to tackle more critical issues.

The emergence of GenAI has literally shifted how organizations think about hiring for specific roles. In the age of AI, organizations are slowly accepting that skills are more important than degrees.

Whereas added skills to handle AI-related aspects of responsibilities are essential for leaders to look into CVs, GenAI unwittingly gives rise to new roles that were otherwise unknown to industry leaders.

The focus is simply having talent to make AI accessible instead of having leaders with degrees and massive business-related knowledge.

For example, the industry aims to onboard talent who can know how to ensure AI model security, ethics, or skills to oversee AI flows.

That’s why the future of work can see more and more people transition to AI specialists, AI data governance specialists, AI engineers, ML engineers, prompt engineers, etc.

Let’s assume that AI empowers us to become more efficient and unleash the potential that machines alone cannot handle.

Till now, the service desk has aimed at SLAs to improve vendor-customer relationships. ITIL-driven practices are integral to service desk improvements; however, they ignore customer and employee experiences.

In the age of AI, especially with the groundbreaking innovation of Generative AI, the focus slowly shifts to experience-level agreement or XLA by making shift-left strategy easily attainable.

In contrast to XLA, SLA only aims to address the issue without ensuring the non-recurrence of the same incident.

Generative AI-based service desks improve agent efficiency, prioritizing shift-left strategy and reducing workloads for the agents by making information more useful and meaningful to solve problems for them in the initial stages.

Whereas SLA is the core part of ITSM, Generative AI makes it easy to improve SLA and helps the service desk transition to XLA effortlessly.

Internal support can involve processes that aim to simplify problem-solving.

Apart from resolving queries, it can also mean augmenting internal knowledge management processes by streamlining repetitive tasks.

Where search engine users might prefer ChatGPT-like responses to Google or other search engines, users can expect hallucinations due to the integration of ChatGPT or GPT-3.5 into their digital workplace. The fact is that LLM-driven support can work with typical or generalized information and not domain-specific answers.

To augment the relevancy and accuracy of enterprise search and information discovery to help solve internal support problems, industry leaders can optimize RAG or Retrieval-Augmented Generation methods to improve text responses.

RAG or Knowledge AI connects to the LLMs you build with your industry-specific knowledge, retrieves the most relevant word that matches the prompt, and plugs it into the LLM to get access to reference text and generate appropriate responses.

RAG-based internal support is best at improving domain-specific search, such as policy rules to get health claims, workplace complinace, PTO balances, etc.

Besides this, RAG can be used to augment the knowledge management process to improve internal support further.

The rise of AI and Generative AI unlocks immense potential impact for marketing and technology—MarTech.

AI has enabled the automation of many marketing activities, translating into streamlined processes and service delivery in real-time.

The first thing that Generative AI can do for marketing is enable hyper-personalization.

Salesforce Einstein is the first product from Salesforce to integrate the power of GPT inside its popular CRM tool to hyper-personalize customer communications.

By leveraging customer insights and analytics through GPTs, marketing teams can automate and streamline marketing processes and derive real-time results.

The workplace predictions in the age of AI for 2024 point toward a massive interest drive towards applying Generative AI to marketing activities and transforming mundane marketing activities.

For example, marketing leaders can fetch analytics and customer data that help create useful recommendations to capture customers’ attention, offer suitable products or services specific to their lifestyle needs, and retain them for a longer time.

Marketing leaders are highly likely to use MarTech with Generative AI as they can use it to automate the creation of marketing materials such as digital ads and personalized marketing copies that include social media copies, print media copies, images, videos, etc.

Generative AI allows immense flexibility to automate and schedule customer emails for follow-up communications.

Similarly, marketing leaders can use an LLM-powered interface to build follow-up interactions through voice or text-based chat, which ultimately reduces friction from the customer touchpoint, keeps them updated, and improves conversions.

GenAI works on black box theory—which means how GenAI produces data or comes to a conclusion is unknown.

On the other hand, GenAI is in its infancy, and it may require industry leaders to learn and evolve with this unique technology to unlock its benefits.

The initial threat landscape, which involves risks like hallucinations and data privacy threats, isn’t trivial.

That’s why industry leaders are willing to make GenAI part of the work process rather than abandon it.

One of the workplace predictions in the age of AI could be implying strict GenAI policies for users.

The first step is to work around the technology and monitor it to make it compliant and harmless.

A policy can define the careful steps to train the LLMs with internal resources, third-party resources, and data cleansing.

Companies want to create policies that upskill their internal people to use LLM apps, interfaces for support, and digital workspaces.

The best thing to harness the power of LLM or Generative AI and derive immense benefits for growth is to build strict monitoring and take steps to prevent future impacts.

Metaverse augments the capacity of virtual and augmented reality. But, its high costs restrict metaverse development.

The excellent news is that GenAI is expected to reduce the cost of building metaverse technologies to reimagine immersive experiences for users.

The 2024 prediction for the metaverse market is $1.4 trillion by 2030, with a CAGR of 31%, as per BCG.

This could make it easy for companies to invest in metaverse use cases and augment the pace of employee engagement.

Some metaverse use cases in the workplace include employee training and engagement and allowing customers to experience virtual worlds for rapid online sales.

The real-world example of metaverse employee learning is to help employees learn new techniques to help themselves keep calm while interacting with customers during unpleasant situations.

Other use cases are to inform employees of the company benefits or allow new employees to take advantage of virtual tours for a more engaging experience.

Metaverse for employee learning and development is thus a prediction in the age of AI to transform employee experience and communications.

Bank of America, for example, is using metaverse tools to augment its customer service experiences

GenAI helps the contact center to evolve as a SaaS experience for users in a better way. With the pace of transformation Generative AI brings with its immense capabilities of language translation, text generation, voice or text recognition, and self-training, experts predict that contact centers can heavily infuse the power of Generative AI with its interfaces.

Gartner predicts that 80% of customer service and support will apply GenAI on top of their customer support channels by 2028.

2023 saw Generative AI become a powerful weapon to transform various business functions, especially in the customer experience area. In 2024, the workplace will likely see massive integration of Generative AI inside contact center tools to streamline every customer interaction process.

Everything looks so easy for the contact center. Agents can automate user customer responses, improve keyword searches to know customer history, and offer better recommendations to eliminate the time needed to enhance the experience.

On the other hand, contact center users can double their experiences by resolving problems autonomously using a rich knowledge repository.

In 2024, businesses want to augment the current state of automation with Generative AI inside their contact centers.

Generative AI is an advanced technology innovation promising to shape customer or user experiences for businesses.

When combined with a customer experience interface, GenAI can give access to immense data points for advanced analytics and customer insights.

Similarly, digital interfaces can be layered on top of GenAI for employee support and capturing data that can help improve employee experiences.

At first, visibility into sheer volume data gives immense opportunity to build data-driven decisions to improve workplace dynamics.

Since employee turnover is a growing pain, businesses can harness data to know where employees face challenges retrieving information or gaining expected productivity levels. Based on data-driven analysis, companies can change workplace policies and make strides to enhance processes that eliminate turnover risks and drive growth.

On the other hand, customer analytics fetched through digital interfaces can help design an intuitive workflow that instantly solves users' problems and delivers maximum satisfaction for long-term client relationships.

The evolution of HR is one of the highly regarded workplace predictions in the age of AI.

HR tech can see massive transformation with Generative AI, automating many critical procedures and reducing user friction from outdated legacy systems.

The ability to recognize simple to complex NLP queries makes it easy for businesses to try GenAI as a copilot to turn everyday workplace queries into workflows and provide a real-time and meaningful solution.

As per the Gartner report, 76% of HR executives believe that if organizations continue to work with legacy systems without Generative AI in the next 2 years, businesses can face challenges to grow.

HR tech can enable many helpful use cases for businesses with Generative AI that solve problems such as PTO queries, workplace policy, and project updates— all with specific domain knowledge.

AI and related technologies like Generative AI or large language model development are taking everything by surprise with their immense capabilities to help extend the creativity level of what humans can do with repetitive work.

Generative AI holds a lot of promise to bring transformative changes to the workplace. Given that GenAI can provide different ways to streamline workplace processes, it is critical to know AI predictions for the workplace in the age of AI, which can help you make appropriate decisions and gain tangible value.

This article's top 10 workplace predictions in the age of AI relate to any workplace scenario—no matter if they use contact centers for customers or service desks to alleviate employee pains. In that case, they can fit easily with business needs and provide a way to build an elevated user experience.

With this, if you want to start and create a seamless workplace experience for your employees, you can try Knowledge AI— an LLM-powered ChatGPT-like interface for enterprise search and autonomous problem resolution.

Get in touch with Workativ to schedule a demo.