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Writing content to attract B2B prospects begins with an understanding of the problems that your prospect is facing, and the solutions that your prospect is most likely to be looking for.

Most AI product firms are founded and grown in a similar way.

It usually goes something like this:

Whether you're a startup or an enterprise, developing AI products is challenging.

Not only do you have to wrestle with the challenges of finding a use-case that where AI can actually deliver value into an enterprise workflow, but you also have UI concerns, and - often - much higher demands to monitor algorithmic drift and other technical issues.

Over the last three years of AI Opportunity Landscape research, we've examined many broad capabilities across the AI ecosystem, from computer vision to conversational interfaces to anomaly detection and beyond. Some of our earliest client research work focused on back-office automation - mostly in financial services and healthcare - and it brought us face-to-face with an array of vendors, use-cases, and opportunities for applying AI for document search and discovery.

Artificial intelligence deployments are fraught with technical and tactical elements that have to be executed well in order to see a return on investment: The data must be accessible, cross-functional AI teams have to work together, and even after an AI pilot seems promising - it often needs to be integrated into legacy systems to be deployed successfully.

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

In July 2017, The State Council of China released the “New Generation Artificial Intelligence Development Plan," outlining China's strategy to build a US$150 billion Chinese AI industry in a few short years, and to become the leading nation in AI by the year 2030. Other nations followed suit quickly with national AI strategies of their own - with the US trailing behind by nearly two years before developing a semblance of an AI initiative. The proposed 2021 budget for the national security budget in the US is $740 billion - with a billions of dollars being earmarked for AI specifically (learn more: US Public Sector AI Opportunity Report). 

What to do when your clients want to cut costs?

Help them cut costs, and be part of a bigger vision beyond cost-cutting.

Supply chains contain every material, component, product and packaging for the objects that together compose the world we live in. However, there is an often invisible ingredient to successful supply chains: data. 

In the last two articles in this 3-part series, we discussed how AI priorities will shift in response to the coronavirus pandemic, as well as how companies can further leverage the advantages they have (and can create) to overcome the challenges they are facing in this uncertain time.