Artificial Intelligence In Big and Smaller Companies
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Artificial Intelligence is eating the world
Technological advancement and digital innovation in the last few years have been instrumental in defining the success of businesses. Artificial Intelligence (AI) has made a huge impact in the world of business in the last decade, as one of the best ways of making processes more efficient and cutting down costs. For organisations of all sizes, knowing where to start with AI adoption can be bewildering, partly because the field and the terminology can seem esoteric. However, it is common knowledge that AI is a key driver of growth in many big enterprises.
Nevertheless, SMEs today are still hesitant to adopt new and emerging technologies such as AI and data science. One of the reasons that make them skeptical is the perception that AI implementation isn’t suitable for small companies due to the lack of resources and adequate funds to deploy AI-powered tools.
In today’s dynamic business culture, you don’t necessarily have to be a big company to reap the concomitant benefits of technologies such as AI.
Instead, AI tools, if used optimally, can completely revolutionize the SME space allowing small business owners and entrepreneurs create highly successful operations across business functions including sales, customer service, marketing, and product” development.
Artificial Intelligence for smaller organizations
For smaller organisations, implementing AI solutions can seem particularly complex or out of reach. There is however great potential for SMEs when it comes to introducing AI. This tends to be because they are either smaller or newer (or both) than established companies, which often have legacy systems in place and may not be able to easily unify the data required for AI systems to work effectively.
SMEs (particularly organizations which have ‘grown up’ in the digital era) often find it easier to gather and integrate data, allowing them to adopt AI solutions more quickly.
Even older SMEs that are not startups and who may be ‘paper-based’ can still think about AI adoption– the key is simply to find a way to get company data into a digital platform.
Business owners and leaders are understanding that becoming digital is no longer optional. True digital transformation is a journey however, and for businesses that want to move into the future and be ready for inevitable adaptation and evolution, it’s much more than a case of sticking on a few technology patches. Business transformation takes discipline, vision and fortitude.
SMEs and AI adoption
For companies just starting out in AI adoption, the most important thing is for management to be on board, because adopting AI into any part of the business will require change. Without the buy-in from the top, there will be too many hurdles to overcome when it comes to financial investment and inevitable cultural shifts.
Business leaders might worry that not being fully ‘tech literate’ is a hindrance to making decisions about AI adoption, but all executives truly need is an appetite for change, an open mind and a willingness to communicate with staff.
For AI to be effective and for business leaders to see the improved efficiency, productivity and insights they are looking for, algorithms need access to good data. Management needs to define the metrics it cares about (for example, more accurate customer outreach? More timely purchasing to reduce overstock and waste?) and commit to making decisions from the data as much as possible.
Knowing what you want to achieve will make implementation more effective and you can start with just one process or area of your business. A commitment to data-driven decision making will ensure you’re collecting the right data; that engineering systems are in place to handle, manipulate and store data; that you value technical and analytical talent; and that you’re shifting the company towards a data-driven and innovative culture.
So, to summarise, there are three key points that SMEs need to know around the implementation of AI:
- Smaller companies might be better candidates for the implementation of AI, due to the absence of legacy systems (unlike bigger organizations).
- Becoming digital is no longer an option. Those who fail to adopt new technologies, will see their margins reduced drastically, whereas their competitors will steal larger part of the market. But change starts at the top level of management, hence it is important to educate decision makers about data science.
- Data is key. Quality data is the main driver of great AI systems. This is having a data strategy in place, is of paramount importance.