The Power Of The Prompt: Unleashing AI’s Full Potential For Work Productivity

By Melody Brue, Patrick Moorhead - August 14, 2023

As AI becomes a mainstay in our daily lives, it promises to be a powerful tool for businesses to improve productivity. AI tools can automate time-consuming tasks, identify patterns in data and even make predictions based on historical trends and behaviors. With the recent explosion of generative AI (GAI), the productivity superpowers of AI are now in the hands of the masses.

Until recently, AI has primarily operated on autopilot – it existed in the background with no human interaction. Previous AI systems were limited to performing specific tasks in isolation, like data analysis or natural language processing without the ability to interact directly with users in a conversational manner. For example, a data analysis AI could process data and provide insights, but users had to manually input queries and analyze the results separately without the convenience of a conversational interface to interact with the AI system

However, we are now seeing a transformative shift with next-generation AI copilots that seamlessly collaborate with humans. As AI continues to reshape the way we work, human-AI collaboration will emerge as the next transformative work pattern, making the ability to work with AI a crucial skill for every employee.

This shift is already underway. According to a Microsoft Work Trend Survey, as of March 2023, U.S. job postings on LinkedIn mentioning GPT (Generative Pre-trained Transformer, the advanced language model developed by OpenAI) are up 79% year-over-year. In the same survey, 82% of leaders said employees would need new skills to be prepared for the growth of AI. In this new era, leaders must emphasize the importance of employees learning when and how to leverage AI, and particularly how to craft effective prompts to generate the most valuable outputs.

The most effective use of GAI relies on providing clear, concise and structured prompts. By doing so, users will make the most of these productivity tools. Let’s look at why prompts are critical for optimizing AI for workplace productivity.

Photo 276214673 | Ai Chatbot © Rokas Tenys
Dreamstime.com

Forbes Daily: Get our best stories, exclusive reporting and essential analysis of the day’s news in your inbox every weekday.

Let’s promptly get to it

The text fed into an AI tool like ChatGPT to elicit a response is called a prompt. The point of a prompt is to take advantage of natural language processing (NLP), which lets you ask a question or give a command using ordinary words and syntax, just as you would with a person. Prompts direct an AI’s responses, so the more thorough the prompt, the more likely the AI will be to produce accurate, in-depth answers.

Using GAI to complete tasks often requires numerous adjustments to prompts, a time-consuming process that diminishes efficiency and productivity. Despite chatbots like ChatGPT’s advanced technical capabilities, users may struggle to optimize their outputs for business purposes if they lack clarity on what specific prompts to provide. This is where prompt engineering comes in.

Prompt engineering enables users to shape the behavior and output of AI models. While this might sound intimidating, anyone with solid writing skills can engineer a prompt to generate needed outputs successfully.

It is worth noting that there are professional prompt engineers—software developers—who train AI models using complex skills. Here, though, we’re talking about everyday users who use a copilot or AI assistant and must learn to communicate their wishes effectively.

New skills for a new way of thinking

According to a recent survey, more than 40% of professionals have already used GAI tools in some capacity as part of their job. These tools support various tasks, including content creation, decision-making and automation, contributing to enhanced productivity.

However, the survey also reveals an interesting trend: 68% of those professionals admit to using generative AI without their boss’s knowledge. This indicates a level of secrecy or hesitation among employees about openly disclosing the use of AI tools at work. This might reflect concerns about job security, fears of being perceived as less competent or uncertainties about the implications of using AI in their roles. In addition, several prominent companies, such as Samsung, JPMorgan Chase, Verizon and Google, have implemented strict policies prohibiting employees from using these applications, citing concerns over possible leaks of sensitive data.

In a recent CNBC All-America Economic survey, 21% of respondents said they were optimistic that AI could simplify their job tasks, while 18% were concerned about potential job displacement. Another 10% thought AI might challenge their roles, whereas 49% believed it would not significantly impact their job responsibilities.

These numbers tell me that people are very curious about AI. At the same time, competency and understanding how AI will affect people’s jobs remain real concerns. Companies and employees alike would benefit from open dialogue about AI and an environment where responsible and efficient AI use is supported. Employees would also benefit from AI readiness training.

How to go from AI-curious to AI-savvy

GAI in the modern workplace is rapidly evolving, with new tools and features being introduced regularly. The good news is that companies like Microsoft are making it easier for people to safely use AI at work by combining GAI capabilities with enterprise-level security in products such as Bing Chat Enterprise. The prevalence of GAI in the workplace and companies’ investment in AI tools will necessitate upskilling so workers can best use the technology.

One of the best ways to achieve this upskilling is by integrating training features directly into AI products. That way, employees can effectively learn how to utilize AI tools for maximum value. This includes training users to fine-tune prompts, leading to better outputs.

There are other ways to promote learning for better AI use. LinkedIn has dozens of free courses on GAI, including streamlining work with Microsoft Bing Chat. I’ve also seen many prompt cheat sheets shared on social media that are quite helpful. There are plenty of good resources out there to help users learn prompt tuning; with a little research, you are likely to surface the right one for your needs.

The importance of specificity in prompts

AI language models can assist workers in generating content such as articles, reports, emails and marketing materials. By providing clear prompts, workers can elicit coherent and contextually relevant responses much quicker than writing them from scratch. Workers can also use well-crafted prompts to quickly extract specific information from vast datasets.

Often, effective prompts require detailed information that a user must repeatedly enter to get better results. For example, for a prolonged session, a prompt might always include “I’m a . I’d like to [specific goal you’d like to achieve].” This sets the context for the AI so it will produce more relevant answers.

OpenAI recently announced Custom Instructions for ChatGPT Plus users. With Custom Instructions, the chatbot remembers user preferences and behavior across different chat sessions. Features like this should save time by eliminating the need to provide context or output preferences repeatedly.

I believe that custom instruction features like this will soon make their way into other productivity tools, making ensuring that AI copilots are better primed for prompts.

Be natural (language processing) in your prompts

To ensure that GAI generates engaging and tailor-made content, users should be as specific as possible in prompts. These prompts are akin to the verbal instructions you might give a person to help direct their efforts in producing written copy, data or summaries. Users can specify the content’s purpose, target audience, desired tone of voice and any essential details like required words, names or hashtags.

For example, if a salesperson wants to generate an email to a prospect, simply entering “Write an email to a prospect to buy Widget X” will produce vague and likely off-tone responses. We must give the chatbot specific information about the email. A successful prompt might look like this: “I am a salesperson at Company A, a maker of [product type]. We have [insert promotion] happening until [date]. With the information provided about Widget X [insert product sheet], write an engaging professional email giving listing the four most attractive aspects of Widget X in bullet points. The email will go to [name of person], a [title, role] at Company B with a call to action to [desired response] within [number] days.”

Providing clear and detailed instructions enables chatbots to better align with your intentions and context, resulting in more precise and tailored responses. Specificity reduces the chances of misinterpretation by the chatbot, leading to irrelevant answers, and improves the overall efficiency and effectiveness of the interaction.

We all need human validation

Embracing the AI copilot era dictates a dramatic shift in our work, which in turn demands fresh AI skills. Collaborating with AI using natural language will become as integral to our workflows as PCs, email and the Web did in previous decades. We must learn how to “talk” to AI to produce the best responses, but we must also remember to validate the answers we receive. AI is extremely intelligent in its way, but it requires human interaction to ensure accuracy and appropriateness.

AI copilots work well by augmenting the strengths of humans with GAI tools in the right contexts. Just as AI providers are constantly improving their models, we need to be sure we’re also improving users’ skills to get the most out of AI. To achieve the heightened productivity promised in today’s AI-driven workplace, we must embrace the power of the prompt. Whether that happens with in-application hints, formal training or intuition developed over time, we’re going to need it to harness the promise of GAI-assisted productivity.

Melody Brue
+ posts

Mel Brue is vice president and principal analyst covering modern work and financial services. Mel has more than 25 years of real tech industry experience in marketing, business development, and communications across various disciplines, both in-house and at agencies, with companies ranging from start-ups to global brands. She has built a unique specialty working in technology and highly regulated spaces, such as mobile payments and finance, gaming, automotive, wine and spirits, and mobile content, ensuring initiatives address the needs of customers, employees, lobbyists and legislators, as well as shareholders. 

Patrick Moorhead
+ posts

Patrick founded the firm based on his real-world world technology experiences with the understanding of what he wasn’t getting from analysts and consultants. Ten years later, Patrick is ranked #1 among technology industry analysts in terms of “power” (ARInsights)  in “press citations” (Apollo Research). Moorhead is a contributor at Forbes and frequently appears on CNBC. He is a broad-based analyst covering a wide variety of topics including the cloud, enterprise SaaS, collaboration, client computing, and semiconductors. He has 30 years of experience including 15 years of executive experience at high tech companies (NCR, AT&T, Compaq, now HP, and AMD) leading strategy, product management, product marketing, and corporate marketing, including three industry board appointments.