Define Your AI Strategy

Update Dec 20, 2020: Produvia now offers custom AI strategies! Scroll to the bottom to learn more.

Your company needs an artificial intelligence strategy to become competitive in a data-driven world.

At Produvia, we believe that businesses, governments, academic institutions, non-profit organizations, national and international research consortia must define AI Strategy to not only survive against competitors but to become market leaders.

We also believe that organizations that create an AI Strategy will establish market dominance in the next 5–10 years.

Follow this document to create your own AI Strategy. Message Produvia to help your team define one.

Artificial intelligence strategy is a road plan for the adoption and implementation of artificial intelligence, machine learning, or deep learning technologies within your organization.

An AI Strategy defines your AI priorities, goals, milestones, mission, and vision.

An AI Strategy focuses on the AI implementation of technology goals while a business strategy focuses on the execution of corporate goals.

AI Strategies are being used in corporations around the world. To date, more than 30 companies have created corporate AI Strategies. These include, but are not limited to: ARM, Accenture, Adobe Systems, Alibaba Group Holding, Amazon.com, Baidu, Cisco Systems, Dell, Deloitte, Google, Hewlett Packard Enterprise, Hitachi, IBM, IPsoft, Infor, Infosys, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, NetApp, Nuance Communications, Nutanix, OpenText Corporation, Oracle Corporation, Pure Storage, SAP SE, SAS Institute, Salesforce.com, ServiceNow, Tata Consultancy Services, Tencent Holdings, Verizon Communications, Wipro, and Workday.

AI Strategies are not exclusive to corporations. National AI Strategies are now being used by more than 32 countries around the world. These include, but are not limited to: Australia 🇦🇺, Canada 🇨🇦, China 🇨🇳, European Union 🇪🇺, France 🇫🇷, Germany 🇩🇪, India 🇮🇳, Italy 🇮🇹, Japan 🇯🇵, Kenya 🇰🇪, Malaysia 🇲🇾, Mexico 🇲🇽, New Zealand 🇳🇿, Denmark 🇩🇰, Estonia 🇪🇪, Finland 🇫🇮, Faroe Islands 🇫🇴, Iceland 🇮🇸, Latvia 🇱🇻, Lithuania 🇱🇹, Norway 🇳🇴, Sweden 🇸🇪, Åland Islands 🇦🇽, Poland 🇵🇱, Russia 🇷🇺, Singapore 🇸🇬, South Korea 🇰🇷, Taiwan 🇹🇼, Tunisia 🇹🇳, United Arab Emirates 🇦🇪, United Kingdom 🇬🇧, and the United States 🇺🇸.

Adapt one of two mindsets when it comes to artificial intelligence: development mindset or research mindset.

Development Mindset

Development mindset, also known as the implementation phase, means you adopt industry best-practices to solve AI use cases. During the implementation phase, you anticipate that all developed AI solutions will make a direct impact on your business. The development of AI solutions typically takes 1 week to 1 year.

Researcher Mindset

Research mindset, also known as the exploration phase, means you apply state-of-the-art methods to solve AI tasks, which may or may not translate to business value. During the exploration phase, you accept that AI solutions may not impact your business. Due to the novelty of your research idea, you accept that your efforts may not impact your business. The research of AI solutions typically takes 1 week to 5 years.

AI teams cannot sit in silos. For artificial intelligence technologies to advance business goals, AI professionals must be embedded in the organization. The most effective AI strategies have been where AI-focused engineers, developers, and data scientists have been embedded into other teams. This cross-collaboration eliminates isolation and allows the business to build multi-functional teams where AI sits at the same table as design, marketing, and sales.

AI must be embedded in every product or service for maximum business impact. At Produvia, we believe that most successful companies adopt machine learning or deep learning into at least 80% of their product or service lines.

You are ready to create your own AI Strategy. What are the next steps?

1. Define your one year corporate and data goals. Corporate goals ensure that you are growing and scaling your business. Data goals ensure that you are accounting for the data requirements of AI solutions. Defining data goals allows you to prepare yourself for any AI solution, whether you develop models or agents.
2. You need to brainstorm AI ideas and use cases. This is not easy. Talk to others, read more about AI, think about what you want AI to accomplish. Think about what data you wish to use in your AI projects. Your goal is to write down at least 5 AI ideas and AI use cases. Don’t worry about the practicality of these ideas or use cases. You simply need to write things down.
3. Focus your attention on select AI projects or initiatives. Narrow down your AI use cases based on business impact. Your goal is to define 1–3 AI projects.
4. Dedicate corporate budget towards AI projects. Each AI solution is different. There is no one budget that suits every project.
5. Hire AI talent. Depending on the project complexity, the number of moving parts, and the speed of execution, you may need to hire: machine learning engineers, deep learning engineers, computer vision engineers, natural language processing engineers, data engineers, software engineers, or data scientists.

Next Step

Are you interested in defining your own artificial intelligence strategy?

At Produvia, we want to create a custom AI strategy just for you!

We will help you define an artificial intelligence strategy with actionable objectives, timelines, and deliverables. With a custom strategy, you will better understand how to leverage AI technologies to be more autonomous in 2021 and beyond.

Complete this form to receive a custom artificial intelligence strategy for only $99 USD!