Enhancing productivity through generative AI

Jul 12, 2023

Key takeaways

Companies are evaluating generative AI to understand how it will disrupt their industry

Generative AI technology will lead the new generation of workplace efficiency

As generative AI rapidly evolves, leaders must understand how to utilize it to stay competitive

Technology risk consulting Data analytics Artificial intelligence Digital transformation Data analytics
Risk consulting Cybersecurity consulting Generative AI Microsoft

Business travelers know the situation well. You have an upcoming meeting in a city you have never visited, and need to book travel. In today's paradigm, you would leverage one or more travel websites and search engines to book transportation, reservations at reputable restaurants and hotels, and then enter times, locations, and activity details in your calendar.

Thankfully, now an AI travel assistant (ATA) can help you accomplish those tasks—including entering events in your calendar. Even better, your ATA can interpret your natural spoken language to create your itinerary.

Example: "ATA, build a trip itinerary for me arriving on Tuesday in Jacksonville, Florida, and leaving on Thursday night. We'll need dinner reservations for three on Tuesday evening and eight on Wednesday evening. Tuesday can be casual, and Wednesday needs to be a professional setting. Also, provide a few choices for hotels that have a 24-hour fitness center and dry-cleaning service on-site."

Your ATA will source online content, including consumer reviews, as well as your personal travel history, to complete the bookings for your three-day itinerary and provide recommendations for additional activities during your trip.

The technology that will soon be enabling these types of comprehensive customer experiences and natural language interactions is a branch of the artificial intelligence family tree called generative AI. It’s the same technology currently revolutionizing the delivery of products and services for many businesses and driving technologies like ChatGPT, Bing search and Google’s Bard. 

What is generative AI?

Many organizations are working to understand generative AI and how to use it. Ben Bilsland, a partner and senior analyst focused on media and technology at RSM UK, described the technology in a recent article:

“Generative AI—broadly—is the use of AI to create new content. However, it is just one form of artificial intelligence that sits alongside a range of other fields, including fuzzy logic, predictive AI, deep learning, machine learning and robotics. The nature of AI means that some of these fields overlap. And whilst AI is typically believed to be a product of scientists starting in the 1950s, we are still at the very starting stages of its scope and potential."

Expanding on Bilsland's description, the emergence of generative AI can be traced to the early 2010s, when researchers began exploring the use of deep neural networks to generate new content.

One of the earliest examples of generative AI is Google's 2015 DeepDream project, in which software used such networks to generate images from existing photos. The resulting images were dreamlike and often included surreal and unexpected features. Amper is another company that tapped generative AI early on, launching software in 2017 that creates custom music tracks for users based on their preferences and desired mood.

Perhaps the most famous example of generative AI is ChatGPT. Developed by OpenAI, ChatGPT leverages an LLM (currently GPT-4) to generate humanlike responses on a wide range of topics. The ATA scenario above is just one example of how this technology will enable new and advanced capabilities in every industry.

The buzz behind generative AI

The team at RSM US LLP's Acceleration Center for Innovation Research Lab believes that generative AI uniquely differs from other technology cycles. A close look at the cycles the team has documented since the year 2000 holds hidden truths:

  1. Infrastructure requirements compound edge use cases.
  2. Innovations are intertwined and build upon each other.
  3. Technology applications are initially dismissed by the majority of consumers and embraced by only a small cohort of technical experts.
  4. Startups leading the initial burst of innovation are surpassed by later-stage startups specializing in the same field.


To illustrate how generative AI is an exception to these four truths, we have to look no further than OpenAI.
  1. OpenAI's technology stack is the edge case of advanced infrastructure innovations, and its application programming interface is the infrastructure requirement that compounds use cases.
  2. GPT-3 and GPT-4 are the combinations of not just one, two, or three domains of innovation but instead consume them all as training parameters.
  3. ChatGPT scaled from no global monthly active users in November 2022 to 100 million by January 2023. In reaching that number, it outpaced TikTok by seven months, Instagram by 28, Pinterest by 39, Spotify by 53, Telegram by 59, Uber by 68 and Google Translate by 76.
  4. OpenAI has received a total of just over $4 billion in funding across six rounds, the largest on Jan. 13, 2023, by Microsoft for $2 billion. Microsoft has since integrated OpenAI's GPT-4 into its Bing search browser.

The ACI Research Lab leverages a scoring model to determine the phase of maturity of new or emerging technology. The team assessed generative AI in November 2022 and again in February 2023. The change in only three months was significant, with the technology advancing from a purely experimental and research phase to the moving of new products and services into the marketplace. Highlights of the team’s findings included:

  • $2.67 billion of funding for Generative AI in 2022 (up 67% from 2021) across 115 deals. 
    • More than two-thirds of generative AI companies have not yet raised a Series A round.
    • Generative AI text captured $825 million of 2021−22 deal flow, with generative AI visual media capturing $822 million.
    • Since 2021, Insight Partners has backed seven generative AI companies, beating Sequoia and Kleiner Perkins, which each backed four.
  • A 198% increase in the number of references to generative AI in scholarly publications year over year
  • Internal interviews on the ways RSM plans to operationalize the utilization of generative AI

Along with earning the dramatic increase in ACI’s maturity score, generative AI has expanded rapidly in the venture capital and startup landscape. As of March 15, $3.15 billion had already been raised across 21 companies in 2023. The deal sizes are increasing, and so are the use cases.

Everybody is going to find value and opportunities using this technology.
George Casey, Advanced Analytics Leader, RSM US

As generative AI matures, funding is expected to not only increase but continue to support the development of highly specialized modules that serve niche business areas. Generative AI will spearhead the newest iteration of workplace efficiency, prompting the next question: How can companies capitalize on this trend?

How can you use generative AI to create value?

As the development and release of LLMs and other generative AI tools accelerates, so too will AI’s role in our personal and professional lives. AI will become part of our tech ecosystems, with new products developed and released in the near future.  For each entry point, we recommend steps middle market businesses can take now to keep up with generative AI while preparing for future opportunities and challenges:

1. In existing applications

Boost the effectiveness of the tech products you currently use by implementing the vendors’ own AI technology, if available, or by integrating third-party AI tools within the products.

  • Example: Microsoft's new AI-enhanced Bing search engine
  • When: Now
  • Steps to take: Research and contact current vendors to understand what's available today. Ask them whether their road maps include plans for AI enablement or integration. Begin researching new vendors if they don't

2. New products that automate specific tasks or processes

New products built on custom or fine-tuned models will replace or greatly supplement existing manual processes. While the industrials and manufacturing sectors have used robotics and automation for decades, LLMs and generative AI is automating knowledge work in new ways.

  • Examples: DeckRobot (for PowerPoint slide decks), DeepScribe (for medical dictation), Headshot Pro (for portrait photography)
  • When: Now; this area is growing quickly
  • Steps to take: Consider which capabilities in your industry might be disrupted by new AI technology. Which of your products or services could be replaced (or supported) by an automated model? Monitor potential disruptors and opportunities for partnership or acquisition. Don't assume the work you do is too niche to be disrupted; AI technology can help startups move in unexpectedly.

3. Integrations and automated workflows

Automate automation? It's possible. LLMs and generative AI will integrate with and overlay today's robotic process automation (RPA) solutions. New solutions will be able to identify opportunities for automation and make the setup of automated workflows even more user-friendly than today's no-code products.

  • Example: Plug-ins for existing tools and data workflows (customer relationship management, new-hire processing, fiscal period closing, etc.)
  • When: Over the next one to three years
  • Steps to take: Inventory the mundane, repetitive tasks being performed internally and continue to prioritize digital transformation. Monitor new products that could automate tasks outside of or overlaid on traditional RPA solutions.


4. Enhanced capabilities and platform approaches

Wide-reaching integrations and new platforms will transform the digital landscape as we know it. Sophisticated productivity tools and AI-enabled search will fundamentally alter a variety of marketplaces (e.g., product selection, learning new skills, trip planning). Today's Big Tech and companies of the future will compete for market dominance and access to the right data on which to train their models.

  • Example: Microsoft 365 Copilot, designed for the workplace, is an early example of this type of solution, which provides simple yet thorough answers to complex questions. Similar solutions designed for personal use will automate actions like shopping and delivery based on prompts like: 

“What is there to do in my area this weekend that costs under $100 for a family of four? After I confirm, purchase all necessary tickets and email them to me.”

“Create a meal plan for two people for five days, based on the ingredients in my smart fridge, and deliver any missing ingredients the day before each meal is planned to be cooked.”

“Find me a physician within my health care network who has been practicing medicine for at least 10 years and has high reviews. Schedule an appointment and add to calendar.”

  • When: Over the next two to five years
  • Steps to take: Imagine how a far-reaching platform, sophisticated information aggregation, or new search functionality could alter your industry/marketplace. What adjustments would you need to make to stay relevant in a new landscape? Consider opportunities such as license deals with larger companies looking to train their models on your data, or how your online presence could be improved to prepare for changes in advertising and search functionality.

Where to begin

Generative AI is so exciting because of the opportunities it will bring across all industries and areas of business. Asked which industries should respond to the recent advances in generative AI, George Casey, advanced analytics leader at RSM US, responded: “Everyone. Everybody is going to find value and opportunities using this technology.” He added that this technology is particularly relevant in the health care, industrials and consumer products industries.

Generative AI is rapidly evolving and will continue to do so as models grow and become more sophisticated. With more advanced models and tools built upon them announced on a weekly basis, middle market business leaders need to think about how—not if—AI will disrupt their industries and how they will utilize the technology, both internally and in their products and services, to stay competitive.

In addition to taking the steps recommended above, business leaders should evaluate the risk and compliance factors involved in adopting AI tools and processes. Companies should begin updating or drafting new policies to account for the new risks introduced by AI, balancing experimentation and advancement with cybersecurity and compliance with legal standards.

RSM provides a range of services to guide your strategy during this critical period of transformation, as well as insights from our blogs:


RSM contributors

  • Zackery Reichenbach-Carr
    Innovation Research Lab Leader
  • Robbie Beyer

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