Introduction – 5 for Friday
Welcome to our August edition of 5 for Friday. In this edition we’re discussing the opportunities for SMEs (Small and Medium Enterprises) to use Artificial Intelligence (AI) within their business.
AI is evolving rapidly, with advances in its application regularly hitting the news, whether in the context of autonomous vehicles, medical diagnosis, deep fakes or many other applications (some positive, others negative). Many of these advances (outside of academia) are being driven by large international organisations, think Google Deep Mind, Tesla, Amazon, Microsoft and co. But how can the bulk of businesses that fit into the small and medium enterprise category benefit from using artificial intelligence both now and in the rapidly evolving future.
In this article we suggest 5 key areas where AI can make a difference to SMEs.
Artificial Intelligence will transform how we live and work, so all organisations, big and small, need a vision and strategy that factors this within their growth plans. To help you on your AI journey we run free interactive workshops to discuss the opportunity for AI within your organisation, helping you create your AI vision and strategy. If you’re interested in a free workshop or want to discuss how AI can benefit your organisations please get in touch by emailing us at firstname.lastname@example.org.
Artificial Intelligence for SMEs
For context, when we refer to SMEs, we’re assuming organisations with less than 250 employees. The five opportunities presented below are achievable by these sized organisations and the budgets that are likely to be available. They’re also valid for larger organisations so please read on irrespective of the size of the organisation you work for.
1. AI infused applications
Increasingly core business applications, such as CRM and ERP systems are encapsulating AI capabilities within them. These capabilities can, for example, provide new customer or business insights, improve financial monitoring or enhance customer communication. Other opportunities are more sector specific, such as automating monitoring of production lines, optimising inventory management or enhancing customer recommendations on an e-commerce platform to name just a few.
Although, not all AI uses add real value (unfortunately, sometimes, suppliers are just trying to tick the AI marketing box), many do. So having a plan to best utilise these new capabilities as they become available within the systems the organisation uses (or as it considers moving to new ones) is important. This will help the organisation stay current and ideally advance how it operates.
2. Conversational AI
Conversational AI provides the ability for people to interact with technology through an increasingly natural conversation. This may be through text based interfaces, i.e. chatbots or messenger bots, or voice based interfaces such as virtual assistants (Alexa, Hey Google, Siri etc) or call-based services.
These capabilities, for example, provide new ways to engage and transact with customers (ideally through an omni-channel experience). Increasingly customers, particularly from the younger demographic, are developing a higher expectation that they can engage with organisations in this way rather than navigate around a website, call a contact centre or interact via email. For the organisation, in addition to providing new communication channels, these increased capabilities can, for example, reduce the demand on customer services and enable a broader range of services to be available 24×7.
For SMEs, there are now many cloud based Conversational AI platforms available with low entry costs. Although, to deliver a good customer experience as well as support a broad range of interactions these platforms need to be trained and integrated. This ‘training’ investment is important, without it, the customer experience will be poor.
In addition to customer interaction, Conversational AI will change how employees interact with technology as well as providing new product opportunities.
So having a plan for Conversational AI should cover all scenarios (customer, employee and product).
3. Intelligent Process Automation
Intelligent Process Automation (IPA) combines AI with Process Automation.
Efficient and effective organisations now appreciate that they not only need a human workforce but also a digital workforce. Where the digital workforce is increasingly performing operations previously performed by people. Often picking up on mundane and repetitive tasks which technology can actually perform quicker, more accurately and more reliably. The human workforce is then freed to engage more with people, handle the more complex and ideally to innovate.
AI is enabling process automation to go beyond original approaches such as robotic process automation. Providing the ability to process documents, understand free text and to make decisions beyond the application of simple rules. This is extending the reach of the digital workforce but also augmenting what the human workforce can do (assisted automation/virtual assistants).
Although some automation platforms can be costly to license and implement, options do exist for SMEs to adopt these technologies successfully with the right approach. Even though smaller organisations don’t typically have multiple people doing repetitive tasks (the original business case for larger organisations), opportunities still exist to use intelligent process automation to improve operational efficiency and performance.
If you want to know more about intelligent process automation then please read our blog series here. Talk to us about IPA, we can help you avoid the pitfalls that too many organisations have encountered.
4. Machine Learning
Machine learning is a core approach within artificial intelligence. It provides the ability for an artificial neural network (mathematical representation of how elements of the human brain work) to learn to recognise patterns, to perform classification and to generate predictions. Machine learning is used by many AI applications, such as facial recognition, autonomous vehicles, telecoms network optimisation etc.
Using machine learning directly (as opposed to using a Conversational AI platform, for example) is applicable to organisations who are data rich. For SMEs, this will depend on the organisation and what it does. For those that do gather lots of data, whether that’s about customers, through their products or by the nature of what they do, machine learning can add significant value. For example, opportunity 1 above (AI infused applications), discussed examples of how AI can become part of product offerings bringing value in terms of what they can do but also adding the power of AI to the marketing message. SMEs can consider this approach for their products or seek to use ML for other purposes such as customer insight or intelligent decision making.
Machine learning is an advanced technology, requiring data science/ML engineering skills that aren’t likely to exist within an SME. Although building an in-house capability may be a possibility for a few, working with a specialist partner may be the best approach for many SMEs.
If raw machine learning is too daunting, one option to consider is pre-trained AI cloud services. These are available from the likes of Microsoft, Google and Amazon and provide API based access to functionality that can analyse content in images, interpret speech, moderate content and more.
We recommend that you seek some external assistance (please get in touch!) before setting off down the ML path in-house as (similar to IPA) many organisations have struggled to take AI beyond initial proof of concept into production use.
5. Augmented Analytics
Augmented analytics brings together AI and analytics, providing the ability to gain greater insight from data as well as helping automate the process of gaining this insight. Augmented analytics is available through data and analytics platforms such as PowerBI (Microsoft), Qlik Sense (Qlik) and Tableau (Tableau). It’s also available through a broad range of specialist platforms that focus on extracting information from certain types of data for example to support marketing (Adverity), competitor analysis (Repustate), customer understanding and sales.
The key here is to appreciate that data has real value, much of which is probably untapped. Using the data the organisations already holds or can readily access can provide insight to transform how the organisation creates, operates, sells and competes. Leading organisations are already doing this and there’s no reason, given the tools available, that SMEs cannot realise the value and benefits their data holds.
We recommend performing a review of your data assets, so that you can better understand the potential value it holds and how you can extract this value. Get in touch if you want to understand how to do this.
If you have any questions about any aspect of this post or AI and it’s application in general please get in touch. Drop us an email at email@example.com and we’ll arrange a call.
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