Is 2018 the year of AI?
Big data on its own is just that, a lot of data. It's what you do with it that counts.
Big data is more than the Internet of things (IOT) and Industry 4.0; it's also about gaining a competitive advantage for your business, in the form of near real-time decision-making. In order to make that happen, you need accurate, up-to-date data paired with big data analytics. You also need the ability to bring together data from a variety of sources and transform it into business intelligence.
Gary de Menezes, Country General Manager, Sub-Saharan Africa at Micro Focus, says: "We're becoming increasingly efficient in the gathering of data, and it's becoming cheaper to process, which is making it more accessible to small businesses as a decision-making tool."
The term 'big data' has been around for a long time. It's nothing new, and neither is the ability to manage or interrogate structured data. What is new is that with the advent of the Internet, social media platforms and mobile phones, the volume of unstructured data has become massive.
De Menezes says: "Over the past 10-12 years we've seen a drive by vendors to come up with a mechanism to bring structured and unstructured data together in a way that allows you to learn more about your business or its customers. In the early days, it was all about knowing more about your business. Today, it's all about knowing your customer and the ability to track your customers across all of the data that you have.
"We find ourselves in an era where we're data rich and information poor. Businesses have all of this data, but the information that they're getting out of it isn't necessarily providing any value."
Against this backdrop, 2018 looks like it's going to be year in which artificial intelligence (AI) will be implemented to gain meaningful insights for business. What is AI? Big data is a building block for AI and machine learning. These days, you can't talk about machine learning without big data, or AI for that matter. Machine learning gave us off-the-shelf AI applications such as voice controls in cars, Siri and Alexa. These are just a few early forms of AI.
"Currently, there's a huge drive around mainstream companies facing threats from agile data culture companies like Facebook, Amazon and Apple," says Paul Cripsey, Presales Director for South Africa at Micro Focus. "These businesses have identified that AI is going to be one of the key business disruptors for them to stay competitive in the marketplace against the new agile data-structured companies that we see coming up. We're seeing it in the South African market too, especially in the financial sector."
"The same companies that are using big data as a disruptor are also heavily invested in DevOps cycles, where changes are introduced every two weeks," says De Menezes. "These businesses use the output from big data, for example, from a forum where customers complain about or compliment a feature or service. They take that output, feed it back and change the product or service accordingly for quick re-release. If the business didn't have the feed of data and the ability to analyse it, they wouldn't know whether a function or feature was popular or otherwise with its customers. You need instant access to current data; you can't just look at your data monthly for this type of quick turnaround."
Buzzwords like smart analytics and predictive analytics all rely on an underlying big data driver. The main transformational forces behind digital transformation are DevOps, IOT, an explosion of hybrid infrastructure, the cloud... all of these are driving digital transformation. If you consider that between organisations and the cloud, companies have access to so much information around customers, their patterns of behaviour, their likes and dislikes. But, despite having all of this information, they often don't know what to do with it. "This is where artificial intelligence can deliver real business results and analysts predict that 2018 is going to be the year in which AI delivers on its promise," says Cripsey.
The bigger the data....
As we've seen, big data is not just information presented in text format. It's voice logs, photos, raw data, data in all of its different fashions, consisting of structured, unstructured and raw data, and it comes from all areas of the business, such as HR, security, administrative. All of this data, when big data analytics is applied, can provide useful insights to the business as a whole, warning of impending disaster or increased demand. One company can have possibly 30 different views of its data, from the perspective of different departments, but all divisions can potentially benefit from a holistic view of that data.
What's needed to accelerate the implementation of AI is cloud and cloud computing. The first wave of cloud computing was pretty much Google and Azure. The second wave was the as-a-service offerings. Now we're seeing the third wave of solutions that include a wider range of solutions such as databases in the cloud. The next wave of cloud computing, predicts De Menezes, will be driven by providers providing APIs to generic AI applications within the cloud. "The cloud has access to so much more data than any company in its own right will ever have."
He reckons that all cloud providers will be offering standard, out-of-the-box AI applications. "With service providers starting to offer AI platforms with existing algorithms that are specific to each industry, business is able to process its big data as a service, bringing down the cost of implementing AI within the organisation. Businesses need to shorten their decision-making cycles. Traditional models of decision-making have to come down in timeframes and become predictive. AI will tell you what you need to do. You're no longer going to review historical data and make a guesstimate based on that. The whole way that we do business is going to change dramatically. AI is definitely going to become a disruptor in the C-suite.
"When you consider the retail environment, for example, the trend is to examine the past couple of years' data, look at buying patterns according to geographical location, then make a guesstimate on what you need to do for next couple of periods. However, retailers have seen poor financial results over the past couple of years. Using AI, retailers can steer customers into a buying pattern by, for example, sending them a message on their smartphone about special offers at a shop that they're currently passing in a mall. AI has the ability to use a smartphone's location data and tie it into the user's buying habits (ie, merging real-time and historical data) and send a relevant, timeous message to that device."
That's where the explosion of AI is going to make a real difference to business in 2018. People are all so busy that they don't have time to go and look for specials that are relevant to them. Facebook already does this, by ensuring that adverts that appear in your feed are relevant to you. It knows where you are and what you're buying - or looking for online - and sends you suitably targeted messages. This is one of the early adopters of big data learning.
De Menezes cites another example, that of Nascar auto racing in the United States. When a race is on, the organisers monitor social media and if they see that viewers at the event or watching at home are unclear about something that's happening in the race, they can adjust their real-time updates to clarify the issue at hand.
Whether it's this type of application or about pre-empting an attempted breach of a system, the important thing is to notify someone and enable people and/or systems to take pre-emptive action based on that intelligence. Whether it's a security issue or about service level delivery, it means that you know what's about to happen.
If you look at the innovation that's being driven using AI by companies at the moment, we're seeing improved decision-making through advanced analytics; businesses are using big data and AI to accelerate the time to market for new products and services; they're improving customer service. However, they're having very low success in monetising their investments in big data and AI; this is proving elusive for most organisations. They aren't yet able to use the data to make more money, but De Menezes feels this breakthrough might come in 2018, with the growing adoption of AI to increase customer spend.
Knowledge is power
Cripsey says: "If you have access to big data but are still doing old fashioned manual analysis, you're doing your business a disservice. You need to know right now whether your business is having customer service issues so that you can take steps to redress this and avoid losing customers."
De Menezes adds: "Once again, this goes to businesses acquiring the ability to do certain things instead of developing those capabilities themselves. In this business environment, you need to be agile if you want to compete with data-driven companies like Facebook, for example. They own so much information about so many people that they can go into pretty much any business they want to, because the chances are good that they have the necessary data around trends in most sectors."
When you consider businesses like Uber and airbnb, they're based on AI, are low on infrastructure, but high on big data. AI is able to help mainstream companies become equally agile and compete on a more equal footing with agile, data-driven businesses.
De Menezes says: "We're going to see a drastic increase in investments in AI, a great number of acquisitions, growth in the technology available and its capabilities, and big data, machine learning and AI will have to co-exist to provide business with the intelligence they need to compete and survive.
However, cautions Cripsey, one has to be cognizant of the inhibitors to implementing AI:
* Cyber security: businesses' data becomes vulnerable and more targeted so they need to be more prepared.
* POPI and GDPR: businesses need to have a grasp of the law pertaining to how they process personal data, and need to take preventive measures to prevent breaches. They also need to be careful what they do with the data to avoid a penalty.