Tuesday, November 12, 2024

The Future of Work: Generative AI in the Workplace

The business world has always been obsessed with efficiency. From the advent of the assembly line to the rise of SaaS technology and automation tools, companies have always pursued ways to streamline operations and boost productivity. 

This has paved the way for the rise of artificial intelligence (AI) in the workplace, ushering in a new era of innovation and transformation. But unlike any technological advancements that came before it, AI’s impact is unique in how expansive and disruptive it is to the workplace. 

Generative AI (gen AI), in particular, is fundamentally changing the skill sets needed to succeed in the modern workplace. While previous technologies impacted select parts of the enterprise space and certain segments of workers, gen AI will impact the entire workplace and every knowledge worker’s role. Similarly, while other technologies introduced new efficiencies and opportunities to streamline work, gen AI offers the same—but also offers to do the work for us. 

This has lead some professionals to fear that gen AI will replace their jobs, however, McKinsey research suggests otherwise. Instead of predicting that AI will take over jobs and leave workers obsolete, they “expect an additional 12 million occupational shifts by 2030.” This means that the future of work will look completely different by the end of this decade.

Companies that survive and win in this changing market will have workforces that know how to collaborate efficiently, effectively, and responsibly with AI. This means that they must act now to prepare for the future of work.

In this blog post, we’re covering the basics of gen AI that you need to know now to prepare for how it will change the way we work. Then, we’re breaking down how we see the future of business communication and workplaces transforming in the coming years.

Generative AI, commonly known as gen AI, is a branch of machine learning in which algorithms and models are trained on large amounts of raw data to create new outputs, such as text, images, or other content.

Unlike traditional AI, which follows predefined rules, generative AI algorithms use machine learning techniques to learn from existing data sets and generate new, similar content. This capability is powered by advancements in natural language processing (NLP) and machine learning, enabling AI systems like Grammarly and ChatGPT to produce human-like text.

Gen AI works in three core steps: 

  1. First, a user enters a prompt. In the context of generative AI, a prompt is the instructions you give the AI to generate a desired output. These instructions can include the content, composition type, tone, length, audience, and more. These parameters provide your AI assistant with the guidance it needs to craft relevant, exceptional writing.
  2. Then, the gen AI tool analyzes the prompt. When the user enters the prompt, the AI tool then processes it using their unique AI model, usually a combination of machine learning algorithms and natural language processing approaches. Natural language processing is a branch of AI that involves teaching machines to understand and process human language (English, for instance) and perform useful tasks, such as machine translation, sentiment analysis, essay scoring, and, of course, writing enhancement.
  3. Finally, the gen AI tool generates a predictive output. The simple way to explain how the AI tool generates its output is to say that it predicts the most likely words or phrases to answer the user’s prompt based on all of the data it was trained on. When we think about the output of the model, it all depends on how the model was designed and trained to provide information.

This may sound simple, but gen AI tools and the large language models that they run are very complex technologies. The power that they hold to transform the ways we work is immense. Let’s dive into some of the benefits that AI presents in the workplace.

The integration of generative AI in the workplace promises to be a force multiplier for highly skilled professionals. These tools have the real potential to amplify employee productivity, enhance creativity, and unlock innovation. McKinsey’s latest research estimates that gen AI has the potential to automate work activities that absorb 60 to 70 percent of employees’ time today. In Grammarly’s latest State of Business Communication report, we found that using gen AI for communication could save up to $1.6 trillion annually in U.S. productivity. 

Let’s take a look at the different benefits of AI across the workplace:

  • Increased productivity: AI automates repetitive tasks, freeing employees to focus on higher-value work and empowering them to achieve more with the same amount of resources.
  • More effective communication: Generative AI personalizes and enhances communication, ensuring messages are relevant and consistent, which makes every piece of communication more effective and engaging.
  • Enhanced creativity and innovation: AI assists in brainstorming, using human prompts to generate new ideas that drive innovation and creativity.
  • Improved customer experience: AI-powered chatbots and virtual assistants provide always-on support, offering quick and accurate responses that enhance customer satisfaction.
  • Enhanced decision-making: AI analyzes large datasets to provide actionable insights, supporting informed decision-making and strategic planning.
  • Employee engagement and well-being: By taking over routine tasks, AI enables employees to engage in meaningful work, increasing job satisfaction and overall well-being.

These benefits are tangible for workers and leaders alike. For workers who use gen AI regularly, 77% say that it makes them better at their jobs. Four in five (80%) workers affirm that gen AI improves the overall quality of their work, and the same percent say they can get more done using gen AI. Moreover, three-quarters (73%) say using gen AI helps them avoid miscommunications at work, leading to benefits like reduced stress, heightened productivity, lighter workloads, and job satisfaction.

For business leaders, over half (52%) note increased efficiency by using gen AI and a boost in overall productivity. Positive performance extends to customer relationship management, where more than a third (37%) of leaders say gen AI has boosted customer engagement. There are also tangible financial benefits, with 38% of business leaders reporting cost savings as a direct result of incorporating gen AI into their workflows. 

Now that we’ve covered the benefits of AI, let’s review some real-world scenarios of companies using gen AI to transform the way they work.

ModMed uses gen AI to boost quality content production

ModMed is a prime example of a company leveraging AI to optimize its operations. Their marketing organization relies on generative AI capabilities to generate quality content, from emails to ebooks, quickly and efficiently, saving each content creator 39 minutes a day—time they can use to focus on high-value, strategic initiatives. As their CMO Adam Riff puts it, “I’m a gen AI evangelist. I love the way it gives people superpowers, so to speak. It takes away work you probably didn’t want to do anyway, like adjusting the tone to sound more professional or finding a new way to say the same thing. Then you can spend more time doing the parts of your job you enjoy.”

Eventbrite uses gen AI to ensure every customer touchpoint is on-brand

Eventbrite utilizes gen AI to enhance the brand experience across every customer touchpoint. They use an AI writing assistant across teams to ensure that every message, from marketing communications to sales emails, is on brand, creating a better overall experience for their customers. Gen AI features provide real-time coaching, context, and suggestions that enable them to become more effective and on-brand in all their communications. Their Head of Content Design, Sami Harvey Reed, outlined two core benefits, “First, it improves communication for our non-native English speakers. Second, it scales Content’s impact to an organizational level in a passive, continuous way by injecting best practices for inclusive and on-brand language.”

Databricks uses gen AI to improve the tone and professionalism of every support interaction

Databricks relies on generative AI to improve the customer experience and resolve issues faster. Their customer support team, most of whom are non-native English speakers, rely on an in-line AI communication assistant to communicate clearly, with nuance, empathy, and professionalism. Their VP of Support, Narsi Subramanian, explains, “If the customer doesn’t have to come back to clarify the questions we’re asking them, you’re reducing the time to solve an issue. I’m not only saving time because things are getting resolved faster, but I’m also very confident that the experience going back to the customer is quite uniform.”

Gen AI is a game-changer for productivity across industries. While that may affect some workers more than others, it will change ways of working for almost everyone. Here are some predictions that we expect to see over the next few years in the workplace:

  • Increased AI integration: Gen AI will become more integrated into various business processes and workflows, from marketing to finance, making communication and operations more effective. We’ll start to see the familiar (and some new) app interfaces that we use today evolve to become AI-powered and assistive. 
  • New competencies: Companies that win will make AI education and upskilling a top priority. Employees will need to develop new skills and improve their AI literacy to augment their work with AI. 
  • More impact on educated workers: Historically, automation has affected workers with lower education and skill levels. Gen AI is flipping the script: more educated workers will likely experience the greatest degree of impact.
  • Enhanced employee experience: AI will help create a more engaging and satisfying work environment by automating mundane tasks and providing opportunities for more creative and strategic work.
  • Ethical considerations: Leadership teams will continue to focus on the ethical use of AI. Companies must ensure that the AI systems their employees use are fair, transparent, and respect user privacy.

A quick note on the ethical use of AI

While the business (and human) impacts are massive, there is an underside that businesses must address. The ethical and responsible use of AI is a critical consideration. Leaders must ensure that the AI systems they invest in and their employees use are fair, transparent, and do not perpetuate biases. This includes:

  • Fairness: If an LLM is trained on unreliable data, such as massive amounts of text data from the internet, which is subject to societal biases, it can reflect or amplify existing prejudices found in its training data. AI algorithms must be designed to avoid bias and hallucinations, ensuring that decisions made by AI systems are equitable and accurate.  
  • Transparency: Companies must be transparent about how AI systems and bots make decisions. This involves clear communication about the data sets used and the logic behind AI-driven decisions.
  • Privacy: Protecting user data is paramount. AI systems should comply with data protection regulations, such as the General Data Protection Regulation (GDPR) in the European Union.

Generative AI is transforming the workplace. It’s not just a prediction, it’s happening today. Gen AI offers incredible benefits that enhance efficiency, communication, and employee satisfaction. 

While there are challenges to overcome, AI’s overall impact is positive. Companies like ModMed, Eventbrite, and Databricks are leading the way in AI adoption, setting an example for others to follow. As AI technology continues to evolve, the future of work will be characterized by increased AI integration, new competencies, and a focus on ethical use. The key to success lies in a proactive approach to embracing AI to create a better, more efficient workplace.

Is your workplace preparing for the AI-powered future? Take this assessment to understand where your business is on the path to enterprise-wide AI adoption and get tips on how to reach the next stage.

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