Over the past few years, artificial intelligence (AI) has achieved impressive market traction. Its progress has been followed by statistics, metrics and adoption rates that put it among the most engaging and important emerging technologies today.
In 2018, a survey undertaken by MemSQL found that companies of all sizes and shapes believed AI and machine learning (ML) to be game changing technologies (74%) that would transform their jobs and the industry. In another analysis by leading research firm, Deloitte, the company found that 83% of early AI adopters had already achieved substantial (30%) or moderate (53%) benefits.
These statistics underscore two of the primary value adds that AI brings to the table – productivity and growth – and are still only part of the AI equation.
Gartner has predicted that by 2020, algorithms will positively change the behaviour of more than one billion global workers, Accenture predicting that the annual growth rates in 2035 will significantly rise thanks to AI, and the list of stats goes on. AI isn’t just here to stay, it’s here to change.
“AI is not a new thing. It’s been present in research labs since the 1960s and was talked about in business throughout the 70s to the 90s, but now it’s gone mainstream,” says Mike Rogers, MD, Enterprise and Security at Tarsus Distribution.
“Because it represents such a low-level, fundamental capability, it has the potential to impact so many different areas of the business today.”
The volumes of data generated by the internet, mobile devices, the Internet of Things (IoT), connected devices, and all the other data points in between, has created vast pools of digital data that can be plumbed for insights. These can then be exploited by AI and ML algorithms to develop powerful insights that the business can use, in near real time, to shape strategy, product development and customer engagement.
Data pools transformed into virtual gold
In the past, these pools of data would have stagnated, the value of the data being squandered because of the overwhelming effort required to manually capture and interpret it. What AI and computing power have done is transform this data into virtual gold that can deliver tangible outcomes and returns on investments.
“AI is permeating business tools across the board,” adds Rogers. “Image recognition and improved scanning and OCR tools are providing higher accuracy rates that result in improved digitisation methodologies and record keeping. This is enabling the digitisation of core processes and improvements in customer responsiveness and real-time structured engagements.”
The technology has been further driven by the commercialisation and mainstreaming of voice recognition and natural language processing tools that allow for any organisation to implement customer service bots that can interact with customers either online or through a call centre.
Increase customer engagement
These solutions can increase customer engagement parameters and the user experience, adding immense value to the business. AI is also increasingly embedded into commercial ERP and CRM solutions and planning tools, the algorithms supporting demand and sales forecasting, budget generation and high-risk customers.
“Using this level of AI integration, the channel can leverage these solutions as value-adds to their customers,” says Rogers. “When implemented correctly, these platforms allow for organisations to identify customers at risk of leaving and then use the human touch to pull them back into the business.
Customer retention through AI
“AI can absolutely be used to help retain customers and manage experiences that put the business on a more competitive footing. When it’s built into a mainstream software package it lets the business learn not only from its own limited set of experiences, but from a massive pool of other customer’s data.”
In the engineering arena, AI models are being used to predict technical failures and manage highly complex systems and solutions. Sensors have already been implemented on planes and trains, with many service providers embedding the AI edge to shift control and maintenance to new levels of competence and security. HP Enterprise InfoSight, for example, analyses and correlates millions of sensors from its globally deployed systems. It learns as it analyses to make deployed systems smarter and more reliable.
“HPE claims that they can predict and resolve 86% of all failures before they happen,” says Rogers. “In cybersecurity, AI is being used to train models to identify anomalous behaviours that could indicate a potential breach. Businesses can no longer rely on signature-based malware identification because the attackers can build tools that morph enough to disguise themselves to avoid detection.”
AI an essential cybercrime-fighting tool
AI in cybersecurity systems has almost become an essential weapon in the war of attrition between threat actor and organisation. As AI tools are embedded into security systems and platforms so they are used by the cybercriminals to evolve their own tools and threat vectors. For the channel, this is a complex environment that does present an opportunity to work with customers in developing solutions and investments that can evolve alongside the security landscape and the organisation.
However, within this morass of technological accomplishment and AI-enabled efficiency there have to be tangible business benefits that the channel can leverage to showcase return on investment (ROI) and long-term value. AI has been immersed in hype so conversations around its deployment have to focus on value, results and relevance.
“AI fundamentally shifts decision making processes, particularly with detection and prediction,” says Rogers. “It allows for the business to learn from other companies and their experiences which makes the process faster and competitively agile. This then allows for intelligent interaction with customers and the unprecedented ability to provider a high level of interaction without massive back-office support.”
AI brings speed and optimisation
AI lowers the total cost of operations through high-volume decision making in real time, replacing manual processes and embedding faster automated solutions. Resources can be intrinsically optimised with AI forecasting and demand planning.
The right tools can ensure the business is able to manage resources across stock, machinery, devices, systems and platforms without the additional staff or time usually required by manual processes and legacy solutions. This also reduces waste, expenses and adds a tick to the much-needed box of reduced environmental impact.
“AI is available and it offers immense opportunity but it’s important that companies differentiate between the hype around AI and whether or not the AI models on offer are going to deliver tangible value to their businesses,” says Rogers.
“Ask questions – was AI simply used to train a static model or does your solution genuinely learn over time? Is the learning limited to the company’s own data set or do they have access to ongoing updates as the software learns from other customers? If the business wants to develop unique AI solutions then they need a deep understanding of the problem and the right people to ensure the right solution is embedded.”
Not a cure-all
AI is not a tonic that cures all organisational ills. It’s a tool, albeit a vastly capable one, that presents both opportunity and threat. Consideration has to be given to the ethics of AI-driven decision-making processes and access to data as much as to the competitive advantage that AI has to offer.
It’s an ever-changing landscape of potential that can help the organisation stand out in a complex market and challenging economy, but it is equally a risk that may not deliver results if not used correctly.
The right partners are key
The right partners and service providers are key to ensuring that AI hands the business the competitive edge it seeks and not a limp liability that skirts the edges of what AI can truly achieve.
AI is working; it’s time to let it work for South African business.