2023 Year in Review


Nathan L. Phipps
Senior Consultant, Wiglaf Pricing

Published December 29, 2023

There have been many events in the last year that have impacted the world of business and pricing. I am going to focus on two developments that I think are most significant: changing economic conditions and the rise of AI.

Changing economic conditions

This time last year, all the experts were convinced that there was a recession on the horizon. It was just a matter of when. I can even recall sharing this “certainty” with friends and family.

Inflation was out of control. The Fed would have to continue the interest rate hikes that they started in March 2022 to rein in inflation. The unemployment rate would rise. Jobs would be lost. The economy would contract.

How wrong we all were. Instead, it appears that the Fed is successfully sticking its desired “soft landing”: taming inflation without throwing the economy into recession. It was recently announced that the personal-consumption expenditures price index (the Fed’s preferred inflation metric) fell 0.1% in November. This is the first decline since April 2020. Prices increased 2.6% this year, which is very close to the Fed’s 2% target. Instead of rising, the unemployment rate fell to 3.4%, the lowest rate since 1969.

What does all this mean for businesses and the pricing community?

Well, lower inflation means that prices for goods and services are no longer increasing as rapidly as they were just a short time ago. There is currently a sizeable gap between consumer’s perception of their personal economics and the reality of their personal economics. But consumer expectations will change as more people realize that prices are stabilizing. This means that substantial price increases will be harder to justify.

But harder to justify does not mean impossible to justify. Focus on your value proposition. Focus on your competitive advantages. Help your customer to understand why your offering has value that justifies a higher price tag.

Is there an opportunity to adjust your commercial policy and optimize your discount management? Can you introduce a segmentation hedge to separate your customers with a high willingness to pay from those with a low willingness to pay, or value-sensitive customers from price-sensitive customers? Is it possible to implement a profit-based incentive structure so that your sales team only makes money when the company makes money, encouraging them to fight for more in sales negotiations?

It may take some creativity, but there is almost always a way to achieve a profit increase of some type, even in your industry.

The rise of AI

The artificial intelligence service that had most people talking this year was ChatGPT, a chatbot developed by OpenAI and released to the public in November 2022. ChatGPT is an example of generative AI: it generates text or images based on prompts that it receives from a user. Subsequent prompts from the user will change the chatbot’s output.

ChatGPT is essentially a sophisticated pattern recognition and generation program. It has been trained on images, conversations with human users, and vast amounts of text (including all of Wikipedia and large portions of the Internet). It can recognize patterns in grammar and use those patterns to generate responses and have humanlike interactions with users.

However, those responses are not factchecked in any way. The rise of ChatGPT also introduced a new term to our vocabulary: hallucination. In the context of AI, a hallucination is when AI generates output that is nonsense or false. Examples of hallucination abound, from making up lyrics to existing songs to generating financial reports of public companies with made-up numbers.

Limitations aside, in the 13 months since its release, ChatGPT has led to a surge in interest and use of AI. Microsoft invested $13 billion in OpenAI in January and started incorporating the technology into their products, including their search engine Bing. And Google, in response to the perceived threat to their search engine dominance, released their own AI chatbot called Bard in March.

All this breakneck advancement has caused some growing pains though. The New York Times recently sued OpenAI and Microsoft for copyright infringement. They argue that they should receive some type of compensation because ChatGPT was trained on their news articles and sometimes provides answers with snippets of their news articles. Some news companies, including the Associated Press and Axel Springer (publisher of Politico and Business Insider), have already signed licensing agreements with OpenAI for use of their content.

Artists are also concerned about copyright infringement as well. At what point (if any) does a chatbot become the creator of an image or song if it is just regurgitating or remixing existing content? There is also concern among some researchers that the technology is advancing too rapidly and safeguards must be put into place to ensure ethical and safe use of AI.

So, a lot has happened on the AI front in the last year. What does it mean for businesses and the pricing community?

Much ink has already been spilled this year regarding the rise of AI and what it means for workers. Prognosticators have foretold a vast range of outcomes. On the one hand, some have worried that the robots will eventually take all of our jobs. On the other hand, some see AI as a tool that will help to augment the efforts of humans and make us more efficient and effective, freeing us from mundane tasks so that we can focus on more profitable tasks.

Personally, I am inclined to put more faith in the latter outcome. Generally, a new technology will cause a loss of some positions that can be easily automated. But it also creates opportunities for new positions, some of which cannot be predicted in advance. Now, that is not to say that this new technology will not cause some pain in the economy. Creative destruction is never a pain-free proposition.

I think that your job is fairly safe if you are actively engaged in pricing offerings and if your expertise lies at the intersection of pricing and strategy. AI is not ready to take over these responsibilities. And it is doubtful that strategy recommendations from a chatbot can be fully trusted without a better understanding of how it reached its conclusions. (Remember the issue of hallucination.) However, you may be in a very different position if you are mostly acting as a price administrator or spreadsheet jockey. The real question is how automatable is your position?

Generative AI excels at mundane tasks such as writing boilerplate emails or writing simple computer code. These are tasks that can be standardized into a routine.

However, generative AI is still falling short on tasks that require human interaction or conflict resolution. These programs lack emotional intelligence. So, embrace your humanity (and the job security it brings) in the coming year!


Banerji, Gunjan. “What Did Wall Street Get Right about Markets This Year? Not Much.” The Wall Street Journal, December 29, 2023. https://www.wsj.com/finance/stocks/what-did-wall-street-get-right-about-markets-this-year-not-much-7d4368fe.

Bruell, Alexandra. “ChatGPT Creator OpenAI to Pay Politico Parent for Using Its Content.” The Wall Street Journal, December 14, 2023. https://www.wsj.com/business/media/openai-to-pay-politico-parent-axel-springer-for-using-its-content-bdc33332.

Bruell, Alexandra. “New York Times Sues Microsoft and OpenAI, Alleging Copyright Infringement.” The Wall Street Journal, December 28, 2023. https://www.wsj.com/tech/ai/new-york-times-sues-microsoft-and-openai-alleging-copyright-infringement-fd85e1c4.

Harrison, David, and Amara Omeokwe. “Prices Fell in November for the First Time since 2020. Inflation Is Approaching Fed Target.” The Wall Street Journal, December 23, 2023. https://www.wsj.com/economy/what-to-watch-in-fridays-spending-report-inflation-closing-in-on-feds-target-0778037d.

Stern, Joanna. “OpenAI Is a Mess. So What Happens to ChatGPT Now?” The Wall Street Journal, November 22, 2023. https://www.wsj.com/tech/so-youre-a-chatgpt-user-now-what-98d2d584.

About The Author

Nathan L. Phipps is a Senior Consultant at Wiglaf Pricing. His areas of focus include pricing transformations, marketing analysis, conjoint analysis, and commercial policy. Before joining Wiglaf Pricing, Nathan worked as a pricing analyst at Intermatic Inc. (a manufacturer of energy control products) where he dealt with market pricing and the creation of price variance and minimum advertised price policies. His prior experience includes time in aerosol valve manufacturing and online education. Nathan holds an MBA with distinction in Marketing Strategy and Planning & Entrepreneurship from the Kellstadt Graduate School of Business at DePaul University and a BA in Biology & Philosophy from Greenville College. He is based in Chicago, Illinois.