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Cost of Change

We read about how large established companies resist change and nimble startups innovate and we see it in companies when we try to bring in a new technology product. Automated buildings are no exception.

Recently with #GenerativeAI, #ChatGPT has created quite a wave with 100 million people chatting with the bot in the month of Jan, the fastest to 100 million user growth record in the Internet. This has created a lot of media buzz about a disruption in the search industry between Google and Microsoft as the latter has announced the integration of a version of ChatGPT into its bing search. Here Google is the established company owning a global search market share of 91.88% followed by Microsoft at 3% of the search market.

Cost of Search vs Cost of a Chat

The cost of a Google search has been measured from public data from Google’s earnings and Internet Usage Stats.

The cost of a Google Search = (Google’s cost and operating expenses)/(Number of Google Searches) which is around $10.7 Billion / 270 to 450 Billion searches = 0.02 – 0.04 $/search (from 2017 data) which has now come to 5 cents for a search with a cost estimate of 2.5 cents per query (based on hardware usage to run servers and compute the query in real-time) while the cost of a chat from ChatGPT is estimated to be 30 cents by the same estimate.Now Dylan Patel of semianalysis has extended this to build out an estimate for the cost of a chat query. here.

How is the cost of a search or chat relevant to Automated Buildings? Or Any Industry?

Well, this discussion about the cost of a chat from ChatGPT replacing the cost of a search is heating up the media world with Microsoft with 3% of the search market is compared with Google with 96% search market because Microsoft has invested in OpenAI and embedding ChatGPT into bing search calling on Google to replace search by chat. This raises the question of comparing the cost of search vs chat and in Google’s case, this is more expensive because if we chat on search it is not going to give search revenues which come from sending traffic to websites from our search. And this is a much bigger challenge for the market leader Google to innovate, mobilize a cultural shift and make decisions and shifts in revenues and business models. This is the typical innovators’ dilemma that established companies face.

Wait, Microsoft is also a big company, isn’t it?

Yes, Microsoft is also a big company. It is playing this game of risk with search which is only 6% of its revenues and 3% of the total global search market share.

Nasrin Mostafazadeh, CEO of the startup Verneek, shared this cost of search vs chat in a recent Rudgers university event from Critical AI about ChatGPT and raised a wonderful point about how technological innovation in the past has always been led by startups in e-commerce, search, social media, etc by companies that then became a big technology company and hence we should look at startups to innovate in the Generative AI space also. Nasrin has founded Verneek to innovate in this space and we should be watching her startup (the author or publication has no affiliation)

This brings us to automated buildings. When you go through technology adoption into automated building space and are looking at Artificial Intelligence and data see the resistance to change from your companies, think about this.

Are they resisting because of the innovator’s dilemma because the change is too big to adapt for the size of the company based on its established culture and employee incentives? Or has the company stopped innovating and is threatened by the new changes proposed with the new technologies? Who is resisting the change, is it some particular product or business unit? What is their reason for this resistance? Will the new proposed technology cannibalize their current business?

I have seen the desktop side of the business in large companies resist the adoption of mobile when iPhone and Android phones were adopted by people and companies had to adopt mobile to support their customer’s behavior change because of this fear of cannibalization of desktop business revenues by mobile.

In the end, large market shifts do not wait for companies or departments inside companies or people to adapt or embrace them. The technology industry has shown that it is not the survival of the fittest, it is the survival of the fastest.

Hope you can use this lesson to urge your companies, clients, and business partners to open their minds and help you address their resistance to change.

With Artificial Intelligence broadly and how smart innovators like Anto Budiardjoare querying ChatGPT for answers we cannot wait or accept the resistance to change.

I asked ChatGPT “what do large companies resist change” and here’s the answer:

== below this is the answer from ChatGPT ==

There are many reasons why large companies may resist change. Here are a few possible reasons:

  1. Complexity: Large companies often have complex operations, and implementing change can be difficult and time-consuming. It may require changes to processes, technology, and organizational structures, which can be challenging to coordinate and execute. As a result, some companies may resist change because they believe it will disrupt their operations and be too difficult to implement.
  2. Risk aversion: Large companies may be risk-averse, preferring to maintain the status quo rather than taking a chance on a new approach. This can be especially true in highly regulated industries or in situations where failure could have significant financial or reputational consequences.
  3. Lack of urgency: When a company is doing well and is profitable, there may be little sense of urgency to change. In such cases, the company may see little reason to take on the risks and costs associated with change, especially if the benefits are uncertain or difficult to quantify.
  4. Cultural resistance: Companies may also resist change because of cultural factors, such as resistance to new ideas, a lack of trust in outside experts or consultants, or a belief that “this is how we’ve always done things.” Changing the culture of an organization can be one of the most difficult aspects of implementing change.
  5. Incentives: In some cases, individual employees or departments within a company may resist change because it would disrupt their own roles or incentives. For example, a new technology might make certain job functions redundant, or a new sales strategy might require a different set of skills than what employees currently possess.

== end response from ChatGPT==

I am pleasantly surprised by the accurate list of reasons from ChatGPT. So let us take this and our experience of dealing with resistance to change and deal with it with the following solutions:

  1. Build internal partnerships with innovative individuals inside the company who are as excited as you about the new technology to join you in testing it with a pilot.
  2. Listen to the resistance from individual leaders and figure out if their incentive structure is hampering their support for you and work out a creative solution.
  3. Find out if the company’s culture is contributing to the resistance and figure out how to create an innovation center or COE to test out new ideas to show ROI to bring to the mainstream business.

Sudha Jamthe is a Technology Futurist who loves mentoring business leaders to innovate and is focused on demystifying Generative AI, the latest hot topic to help business leaders understand it with her upcoming book “Generative AI: A Primer for Product Manager and Business Managers” now available for pre-order on Amazon.