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3 key considerations for AI in corporate strategy

As artificial intelligence leaves its mark on an ever-widening group of industries, teams will need to adapt their corporate strategy to stay ahead.

From healthcare to manufacturing, artificial intelligence is well on its way to impacting every industry. Whether its AI-driven platforms that improve population health through aggregated data or industrial robots that achieve perfect accuracy and speed through repetition, these seemingly futuristic images are now an increasingly common part of our personal and professional lives.

This shift has never been more evident than with the recent boom in generative AI, brought about by tools like ChatGPT, a free-to-use open AI platform from OpenAI and subsequent, more commercial offerings like Copilot from GitHub and Bard from Google. While generative AI has lost some momentum due to possible regulatory changes and the involvement of larger tech companies, it has the potential to make a return, and there are plenty of other artificial intelligence use cases gaining steam and actively transforming the way we work and live.

As more corporate teams research and integrate artificial intelligence, it’s becoming evident that the impact of AI isn’t solely limited to creating new AI-enabled products and services. For many businesses, AI also represents a vehicle for improving their business on an organizational level, supporting areas like market analysis, risk management, and innovation. As AI augments or replaces existing software in an ever-widening group of industries, teams will need to adapt their corporate strategy to stay ahead. Here are three reasons your team should consider making AI part of your strategy:

1. There’s no slowdown in sight

In recent years, advances in deep learning have resulted in an influx of AI applications and laid the groundwork for additional progress in the field. This technical growth, paired with greatly increased visibility and accessibility through generative AI, has helped artificial intelligence gain traction with a much broader market. Despite signs of downturn in the broader VC space, funding for AI remains consistent, accompanied by an active AI exit market. Corporate VC is also a large part of this shift, as larger tech companies continue to enter the space en masse through AI-focused funds.

With the assurance that this technology will continue to experience growth and support, teams must be prepared for the eventuality that their industry and the industries correlated to it will feel its effects. Even if your team does not plan to adopt an AI solution, does it have a plan for competitors that do?

The rise of artificial intelligence


VC capital raised since 2020


M&A capital raised since 2020


VC deals since 2020


M&A deals since 2020

A selection of corporate AI-focused funds

GPU Venture Program
Announced March 2009

Gradient Ventures Fund
Launched July 2017

Salesforce Ventures AI Fund
Announced June 2018

How will regulatory changes around generative AI affect VC funding?
Read our Q4 2023 Analyst Note on Generative AI

2. The competition will gain an edge

Corporate venture capital isn’t the only way businesses are getting in on AI; they’re also increasingly focused on M&A opportunities in the space. In 2023, pure-play AI solutions outperformed conglomerates, making them an appealing target for vertical integration, especially as AI semiconductors and other AI infrastructure companies continue to thrive in the market. The last several years have seen a substantial uptick in liquidity and a healthy exit environment driven by strategic acquisitions—signs your competition might already be one step ahead.

In assessing the impact of AI, consider your industry’s receptiveness to the technology and what they could stand to gain from it. How could being an early adopter help your company differentiate itself and potentially pull out ahead in the market? How quickly could a competitor put together and execute and AI plan and what advantages would it magnify if successful?

Active acquirers in the space

27 AI and machine learning investments, including AI.Music, A.Team, and WaveOne.
Last deal date: October 5, 2023

19 AI and machine learning investments, including Aleph Alpha, Articul8 AI, and Stability AI.
Last deal date: January 9, 2024

15 AI and machine learning investments, including Graphcore, Omnidian, and Syntiant.
Last deal date: November 8, 2023

14 AI and machine learning investments, including Doppel, Gus, and Photoroom.
Last deal date: January 10, 2024

Cisco Systems
11 AI and machine learning acquisitions, including BIOS, Samay, and ZestIOT.
Last deal date: September 29, 2023

Noteworthy AI acquisitions

Anthropic, a San Francisco-based AI safety and research company, raised $4 billion in late-stage VC in a deal led by Amazon in September 2023. It has raised $7 billion to date and is valued at $25 billion.

Cognigital, a transport AI company based in Birmingham, England, raised $631 million in Series A venture funding from undisclosed investors in September 2023. It is currently valued at $47 million.

Databricks, an AI development platform headquartered in San Francisco, raised $684 million in venture funding in a deal led by Nvidia in November 2023. It has raised $4 billion and is valued at $43 billion.

3. It will increase operational efficiency

Although the rise of AI is not without controversy, the technology has undoubtedly opened the door to new operational efficiencies and potential team proficiencies. It can help patch up areas of weakness, close the gap with competitors, or simply amplify what your team is already doing.

As you evaluate AI’s potential benefits to your business, don’t look at it only from the perspective of generating net new output, but also how it can eliminate pain points too. Using AI to remove parts of the process that are especially time-consuming, prone to error, or hazardous can represent significant improvements to your business.

Whether it’s easing the burden of menial tasks, streamlining operations, or automating difficult decisions, AI is already making workplaces run more smoothly than ever before. Here are just a few examples across three diverse industries:


AI technology helps farmers detect pests, optimize crop yields, monitor soil health, and predict environmental impacts. These agtech-enabled farming methods promise to improve food security in the face of climate change and population growth. Startups developing AI solutions for agtech include AIS, FarmWise, and Root AI.


Personal healthtech AI assistants for physicians and nurses recall medical research, compile patient data, provide initial diagnoses, and optimize workflow—while deep learning algorithms help doctors detect and diagnose certain cancers and diseases. Examples of these startups include Atomwise, insitro, and PathAI.


To meet legal and regulatory requirements, many firms now use AI-driven platforms to automate filings, review documents, and conduct legal research. Some applications even analyze data to forecast the outcomes of proceedings. Examples of AI startups in the legal space include Evisort, Harvey, and Luminance.

Given AI’s breathtaking rise, every company needs to plan for it. So far, most corporations have simply ignored its potential, while others have been remarkably slow to react. Although it’s not too late to catch up, companies that hesitate or delay will find it harder and harder to compete with rivals who have evolved into well-outfitted, well-oiled, AI-driven machines.

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