Tech Companies, AI Initiatives and Agribusiness Implications
An overview of tech company AI initiatives and the potential implications and opportunities for agribusinesses.
As highlighted in The Long Tail of AI by Contrary Research, artificial intelligence is not the central part of the vast majority of businesses, but most companies will be impacted by developments in AI technology.
This long tail is directly applicable to agribusinesses:
How will advancements in artificial intelligence impact agricultural companies whose business models and practices have long predated AI tools like ChatGPT?
How are employees across the agricultural sector, from agronomists and researchers to operations managers and supply chain analysts, using artificial intelligence today? How might they use artificial intelligence in the future to enhance productivity, decision-making, and resource management? Where do they want to access these systems?
How are agricultural companies positioning themselves in the AI marketplace? Are they building proprietary AI models tailored to agriculture, or are they leveraging third-party tools to support these applications? How should agricultural companies be strategically positioning themselves within the rapidly evolving AI landscape?
The answer depends on whether it is an agricultural software company or a crop input/equipment manufacturer or an ag retail/dealership, however the point is that there is a need to understand and think through employee workflow, customer demands and product and support functionality to identify where challenges can be solved with AI.
But that’s just one component.
I believe it is important to understand what is occurring within the largest technology companies, the enablers, surrounding artificial intelligence to glean deeper insights into what the implications might be in the short, medium and long term for agriculture and for agribusiness professionals.
Much like I do to understand the agriculture industry, I turned to earnings results and earnings call transcripts for pieces of information and context that could signal a trend or be important in assessing what comes next.
Below you’ll find notable quotes, facts and figures surrounding artificial intelligence initiatives from the major technology and AI players along with additional commentary from me (where applicable) on what the potential implication might be for agribusiness professionals and enterprises.
Index
Apple
Amazon
Alphabet
Meta
Microsoft
Salesforce
ServiceNow
Apple
The main goal of Apple’s AI efforts is to increase upgrade rates and reduce cycles between upgrades of the iPhone and other devices.
Implications for Agribusinesses: For agribusiness professionals this primarily means the potential for Apple Intelligence to improve their efficiency on their phones.
Apple’s approach is built with privacy in mind as a key aspect of their AI initiatives
Apple Intelligence marks the beginning of a new chapter for Apple Innovation and redefines privacy and AI by extending our groundbreaking approach to privacy into the cloud with private cloud compute. We made the first set of Apple Intelligence features available in U.S. English for iPhone, iPad and Mac users with system-wide writing tools that help you refine your writing, a more natural and conversational Siri, a more intelligent Photos app, including the ability to create movies simply by typing a description, and new ways to prioritize and stay in the moment with notification summaries and priority messages.
Apple sees a ton of interest in Apple Intelligence.
Their figures back this up, too:
If you just look at the first 3 days the 18.1 adoption is twice as fast as the 17.1 adoption was in the quarter a year ago...So there's definitely interest out there for Apple Intelligence.
Tim Cook notes that there’s a lot more to come with Apple intelligence, including visual intelligence and the ChatGPT integration:
Apple Intelligence, which marks the start of a new chapter for our products. This is just the beginning of what we believe generative AI can do, and I couldn't be more excited for what's to come.
AI investments
Relative to others in this space, Apple hasn’t ramped up their capex. It is around $10 billion per year.
We are rolling out these features, Apple Intelligence features already now. And so we are making all the capacity that is needed available for these features… in fiscal '25, we will continue to make all the investments that are necessary, and of course, the investments in AI-related CapEx will be made.
In terms of R&D as a percentage of spend, Apple is at ~8% (~$31 Billion), and when asked whether this may go up, they responded that the AI focus has increased, but they’ve reallocated headcount towards AI.
As we move through the course of fiscal '24, we've also reallocated some of the existing resources to this new technology, to AI. And so the level of intensity that we're putting into AI has increased a lot, and you maybe don't see the full extent of it because we've also had some internal reallocation of the base of engineering resources that we have within the company.
Amazon
Amazon’s AWS AI businesses is growing well:
In the last 18 months, AWS has released nearly twice as many machine learning and gen AI features as the other leading cloud providers combined. AWS's AI business is a multibillion-dollar revenue run rate business that continues to grow at a triple-digit year-over-year percentage and is growing more than 3x faster at this stage of its evolution as AWS itself grew, and we felt like AWS grew pretty quickly.
At the same time, they note that given industry and market dynamics, margins on the AI side are lower than the rest of AWS:
It's moving very quickly and the margins are lower than what I think they will be over time. The same was true with AWS. If you looked at our margins in 2010, they were pretty different than they are now.
It is interesting to note growing margins, which also signals lowering costs, which continue to decrease.
Beckrock
Amazon Bedrock is a platform within Amazon Web Services (AWS) designed to help developers build, customize, and deploy Generative AI (GenAI) applications. It provides easy access to a broad selection of foundation models from various leading AI developers, allowing customers to fine-tune these models with their own data and integrate them into their applications without having to manage underlying infrastructure.
Amazon is bullish on its Bedrock system. It boasts modules for evals, guardrails, RAG and agents, and the broadest selection of foundation models:
Recently, we've added Anthropic's Claude 3.5 Sonnet model, Meta's Llama 3.2 models, Mistral's Large 2 models and multiple stability AI models. We also continue to see teams use multiple model types from different model providers and multiple model sizes in the same application. There's mucking orchestration required to make this happen. And part of what makes Bedrock so appealing to customers and why it has so much traction is that Bedrock makes this much easier.
Agribusiness Implications: