Better decisions, fewer risks in a future world - deploying AI securely

Opinion by Sean Harrison-Smith

The business world has been battered by successive waves of new technologies, but Sean Harrison-Smith says they need to take the risk now and deploy AI and big data for cyber-security as it may lead to fewer risks in the future.

Life has become strange recently. On the world stage all the talk is about building boundaries, walls and restricting trade. Yet in business, we're still discussing the benefits of breaking down barriers, integrating siloed information, open systems and global markets.

We're even experiencing an end to the traditional 9 am to 5 pm office day as a more and more opt to work remotely. In other words, conventional restrictions are being smashed and the momentum is so strong that it's hard to imagine it won't continue to grow.


But then who knows? As we have learnt over the past few years, anything can happen and businesses need to be prepared for a potential bumpy ride. But the difference now, compared to whenever this has happened previously, is that advances in analytics and artificial intelligence (AI) means better-informed decisions leading to less risk-taking.


While the security industry may sometimes bemoan the fact that everything is being connected to the internet, and that all our variable data sets, being interconnected, risk infection from one to the other, and provide routes for attackers to work from vulnerable low value areas to the better protected high-value data - its a move that is only going to continue and accelerate.  By explaining why this trend is here to stay, we can adjust our thinking to ensure we secure this new way of doing business, utilising AI and big data, recognising that we need to influence how things are done - because we are not going to stop what is being done.


According to Salesforce, despite all the data we are currently creating, less than one percent is currently analysed and half of all business decisions are made with incomplete information


But perhaps the main step change is not that AI, for example, exists at all – after all it's been backbone of science fiction for decades. The leap is that it's now accessible to smaller businesses, providing tools that don't just pull information out of data, but push information to you, anticipating what you are going to want to know.


So what has brought about this change? In the past there has been four key challenges to using AI in business:


  1. Unconnected data

Most business data sits in a maze of internal and external systems and a mix of cloud and on-premise systems which don't communicate, leading to siloed data and questionable data quality. Cloud-based CRM solutions are designed to connect all of that data to create a single view of each individual customer. This connected approach to data is essential to optimise the AI opportunity.


  1. Overcoming skills shortages

Unanalysed, unused data is worthless. So data sitting in these silos is no good to anybody. But neither is data that nobody can analyse or make meaningful in any way. Data scientists are like gold dust and can ask for their weight in gold accordingly. But today's new AI tools are making it possible for businesses to work without them, although I don't think they'll be taking a pay cut soon. The best new platforms offer native data preparation, saving time and resources by eliminating the need for ETL


  1. Cloud cuts through the cost

Previously the kind of computing system needed to run machine-learning algorithms would have been prohibitive for small businesses to buy. However, cloud computing has made this computing power more accessible and affordable.


  1. A world away

Until recently, AI was something that existed in books and in films – nothing to do with business. And yet why are the tech giants all developing their own form of AI – for example Salesforce and Einstein, IBM and Watson? Because they see the huge potential, of course.


But how does AI differ from just analysing data?  Algorithms adapt to data, developing behaviours not programmed in advance, but learning to read and recognise context. Inherent in this is the ability to make predictions about future behaviour to know the customer more closely and to be proactive rather than reactive.


And how does it work in practice? For example, a manufacturer may be thinking of increasing production – instead of just shouldering the risk, increasingly they will have metrics and predictive data to tell them whether or not this is a good idea.


On the sales front, reps can be ‘pushed' proactive information on their day ahead on a smartphone or tablet. Key customer meetings are organised in priority of opportunity value and along with each of their top three pain points plus practical information such as directions to a customer site (which is also pre-programmed into the rep's sat nav). This information is dynamic; for example, suddenly there is a notification; a top customer has just made an important acquisition. Automatically the rep is sent the top trending news articles on the topic with product recommendations that integrate with the acquisition.


Meeting notes are uploaded and the system automatically extracts action items and suggests next best actions.


There's little doubt that the impact of AI for business will be pervasive and cover many areas including sales, service, marketing, manufacturing and even IT where it can be used to build smarter, predictive apps faster.


Salesforce may be the first of the big names to consolidate all their acquisitions and bring the results to market but the software is still evolving and will, no doubt continue to do so. Salesforce partners have a huge role to play here in working with customers to first show them that AI will complement their skills to help them work and act smarter and then help them implement the technology in the best way for their organisation.


It's not surprising that some organisations are wary: the business world has been battered by successive waves of new technologies over the past few years. But perhaps taking the risk now, may lead to fewer risks in the years to come.


The cyber-security industry has to lead the adoption of AI and big data, deployed for our protection, recognising that its the new business as normal.


Contributed by Sean Harrison-Smith, managing director, Ceterna

*Note: The views expressed in this blog are those of the author and do not necessarily reflect the views of SC Media or Haymarket Media.

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