How To Succeed With Enterprise AI: Buy Vs. Build

Companies in every industry are expanding their efforts in AI. Companies are beginning to understand the strategic imperative to use AI to their advantage before their competitors do. (See “The AI Threat: Winner-Takes-All”).

As a company leader, you need to address several critical questions:

●     What is the best way to adopt AI within our company?

●     How do we invest in AI with the greatest chance of success?

●     How can we be nimble and quick in rolling out AI-based initiatives?

●     Should we build or buy our AI solutions?

Many companies will want to implement AI with their own teams, their own data, and their own systems. In most cases, that will be a mistake. Here is why you should buy your solution vs. build it all by yourself.

The Talent Challenge

Top talent in the AI world is overwhelmingly being hired and retained by successful technology companies. Today (according to the TalentSeer 2020 AI Talent Report), if you want to hire AI engineers, you must be willing to pay north of $350K in total compensation to win against Amazon, Google, Microsoft, Facebook and many growing startups.

By some estimates, Facebook and Google alone employ 80% of the machine learning PhDs coming into the market.

Not only is it difficult to compete with the biggest and most successful technology companies for AI talent, but it will only get harder. The big technology companies are enticing AI professors themselves to join their companies, leaving a gap in the market for teaching AI at universities. This makes it even more difficult to find qualified students with the knowledge and skills you desire.

You can't give up completely. It's important to hire some AI talent, even if you won't get all you need. Your internal team needs to create an infrastructure of people, training, and systems and (usually) a Center of Excellence. Staffing for these areas is important, and you should strive to get AI talent to build the minimum viable AI team on board.

Once you create your minimum viable AI team, there will be a big focus on working with outside vendors to choose, implement, and manage AI-based solutions. The three primary categories of vendors your team will need are those that will help with AI platforms, AI products, and AI consulting companies. Let's look at each major category of vendors you will want to buy from.

AI Platforms

An AI platform exists to bring together a variety of tools into a single environment. This enables the tools and data to work together and exchange information seamlessly. Sometimes called AI Platform-as-a-Service (AI Paas), the leaders in this space are Amazon, Google, Microsoft, and IBM.

AI PaaS is a set of AI and machine learning services for building, training, and deploying AI-based functionality and applications. Essentially, AI PaaS provides you with almost everything you need from an infrastructure standpoint to get your work done.

Examples of other solutions that can provide AI PaaS solutions include:

●     TensorFlow - open-source,

●     Petuum - ease-of-use,

●     NeuralDesigner - neural networks, and

●     DataRobot - visual interface.

AI Products

AI product vendors provide AI solutions that can sometimes work on your infrastructure but often are best paired with an AI platform.

Fortunately, the world is rich with choices in this arena. AI product vendors tend to focus on a particular function within an organization or a vertical market. The list of functions and verticals is too long to provide here. I will share a select few to give you a feel for what is available and link to a comprehensive list here.

In B2B Sales & Marketing

●     Clari - sales analytics and forecasting

●     Anaplan - real-time enterprise line-of-sight

●     Tact.ai - AI-powered assistant

In Productivity

●     WorkFusion - automate business processes

●     X.ai - share availability and schedule meetings

●     Verbit - for captioning and transcription

In Security and Risk

●     Splunk - IT operations

●     Deep Instinct - cybersecurity prediction models

●     SentinelOne - endpoint security

In Finance and Operations

●     Zest AI - credit underwriting

●     Personetics - personalization for financial services

●     Kasisto - conversational AI for banking and finance

AI Consulting Companies

Whether you buy or build, you can benefit from using outside experts to help make the right decisions and implement your solutions. AI-focused consultants fall into a few main categories:

Strategy

If strategy consultants understand your overall corporate strategy and your unique challenges and opportunities, they can help you identify the most important AI initiatives for your company. The major strategy firms include McKinsey, Bain, and BCG.

Strategy and Implementation

Other large players will offer a combination of strategy and implementation services. This combination can be particularly effective. These firms include Capgemini, Accenture, Deloitte, PwC, EY, and KPMG.

Implementation-focused firms include:

·     Element AI - building customizable machine learning solutions

·     ProKarma - enterprise applications

·     Cabot Partners - deploying AI/ML solutions

·     Fortress IQ - governance for business automation and AI

·     Atrium.ai - customer experience focus

The vast majority of enterprises creating AI-based solutions will not be able to hire all the talent they need to create their unique solutions. The optimal way to address this talent shortfall is to get help from companies focusing on AI platforms, AI products, and AI consulting services.

Now is the time to begin buying what you need to take advantage of the opportunities to win in your market with AI.