Building an AI-first company, are we ready- Hays careers advice Viewpoint careers advice blog

Building an AI-first company, are we ready- Hays careers advice Artificial Intelligence (AI) in its short form is currently one of the most common phrases entered into search engines.  This Google Trends graph  suggests Artificial Intelligence popularity to be reaching the same level as it was in 2004, following the release of science fiction movie I, Robot starring Will Smith.  I am in no way attempting to compare the popularity of Will Smith to the current interest in AI, but time has proven that what was once science fiction, is now becoming real. AI has started to become more tangible and can be put to good business use by AI-first organisations. There are a lot of interesting views on whether AI is a threat or an opportunity, or whether AI needs to be regulated, a topic which we have already explored in depth. I now believe it’s time for businesses to take this opportunity and embrace AI for business transformation and growth.  I feel excited because AI has started to travel from the world of academia comprising of computer scientists, physicists and mathematicians, to the wider world of business and consumers.  AI has the capability to shift the productivity and revenue dial for a lot of companies by significant margins. I am lucky to be a part of influencing some of the first strategies; mobile-first, API-first and cloud-first, and also see the benefit of implementing these strategies. Based on my experience, here are the four key areas to focus on if you want to become an AI-first company, and gain a competitive advantage: 1. Build an AI-first culture This is the most challenging and important part of transformation, the part which will get people ready for the new and exciting world of AI. The end product will end up on the lap of end users, be it consumer or employees. If businesses really want to thrive in this exciting age of AI and data powered systems, they will need to invest in its people to train and use the products built with AI technology. A good training plan, group learning boards and exercises will help employees to trust the output of the systems and use it as a companion to make the decisions on their behalf, and this trust is key to building an AI-first company. Someone of great wisdom said to me once that “if you think you are not a software company you may not be a company in future”, so like all good software companies, every employee should be encouraged to embrace AI. 2. Existing products and tools â€" looking through an AI lens   One of the keys to becoming a true AI-first company is looking at all products and services you offer (B2B and B2C) through an AI lens. All existing products, software, tools, services used by employees, offered as B2B and B2C engagements can be assessed, made smarter or replaced by AI. Take  recruitment for instance, are you still stuck with developing a tool which can only search based on keywords and fields entered by a recruiter? AI enabled search can transform this system by getting trained to generate the searches for our recruiters rather than recruiters having to search and find top candidates for a given job. Are recruiters still having to arrange an interview manually, or do you have an AI assistant who can do that for them? Are you having to respond to emails yourself while there are so many AI services which can help generate “smart replies”  which are passed onto you to edit and send? There are many such use cases and applications in various industry domains and products which, if applied, can bring some serious productivity improvements.  So, understand the existing products, look at them through an AI lens, plugin AI services and transform the culture and usage. Obviously, once you have evaluated this you need an AI architecture to integrate and enhance existing products and services, but that’s a separate blog altogether. 3. Develop an automation culture and approach In software, we always used to automate something if we knew that the process was predictable, could be documented and was less laborious than doing the process manually. This approach meant most of the time, the percentage of automation possible was claimed to be 50-60 percent , but practically it translated to 10-20 percent. The advent and availability of AI-based automation facility transforms and changes the whole of this past approach to automation. Automation no longer needs to be based on a scripted well-defined process, but a machine which is trained to perform a task as a normal human being would do. The automation can now handle most of the exception scenarios on a massive scale. Although it sounds like a simple thing, it has a very deep impact on automation and again points at numerous use cases which I am sure we are already seeing or will see soon as products in the marketplace. For example, one of the common use cases for IT services was automated software testing. AI will harvest a product which can act as a robotic tester for all of your software products and releases instead of software testing automation. Similarly one of the areas where AI can help and transform now is manual data entry into the system. An example within the recruitment world could be creating a well-tagged/classified job and candidate profile in the system by a user. In other industries automation use cases could be creating a customer record in the CRM system and tagging them with the right business section/department, recording a call log in the system, etc.  These are very promising automation use cases and close to reality where systems for end users will not be to perform grunt work but rather produce meaningful output for them. So assess what problems your business users and employees solve on a daily basis, and take the grunt work away from them with automation powered by AI. 4. Develop unique data propositions This is the key to AI strategy and the only one which will give any business a competitive advantage in the long run over others. AI-based products and services are a combination of Algorithm + Computing Power + Data. AI and machine learning algorithms will be open to all, computing power is available in abundance and cheap on the cloud, however, the data points generated in the company are the unique and key differentiator. A good data strategy and partnership which can create a unique data set to deliver a use case powered by AI algorithms, sitting on top of the combined meaningful data store, will have a competitive advantage. The businesses who nurture and care for their unique data points and formulate an intelligent data strategy will have the upper hand. AI is a very vast and broadly used topic these days. I hope the above article gives you a basic approach to start acting and using AI to best of your business advantage and take your first step to being a true AI-first company. You can read more digital transformation insights and advice below:   Ensuring digitalisation in your business is a success Forget about the robots â€" four practical ways to stay relevant AI Will Be a Big Part of Our Future â€" but What Does That Mean for Businesses Searching for Talent? SMEs-you need to fix your digital skills gap Automation: Job killer or temp job cultivator?