AI will catch on faster than Smartphone
The effects of smart algorithms are manifold
Artificial Intelligence (AI/AI) is both over- and underestimated. Overestimated is the “intelligence” of systems that is still miles away from human intelligence. Underestimated are the effects of intelligently used AI algorithms and the speed with which AI processes, customer relationships and the entire company will change..
Admittedly, there were already AI euphoric times in the 60s and 80s of the last century. Today, analysts call the long phases in between AI hibernation. In the euphoric phases of the past, similar AI dreams and nightmares were spun as today. Terminator and HAL from Kubrick’s film epic “Odyssey in Space” send their regards.
The big difference to today: We now have the necessary technology and with cloud and serverless computing a very flexible infrastructure that can accommodate the extremely CPU- and memory-hungry AI applications. And above all, we have the data that AI needs to learn and recognise patterns that are often hidden from us.
At the same time, we ourselves have created the need for AI applications. Our world, both large and small, is now so complex that we cannot master it in the long term without much more extensive analysis and automation of processes. This applies to almost all areas of human life, at least in the industrial nations.
The three elements opportunity (CPU + cloud), demand (digitalisation, complexity) and motive (productivity increase) will ensure that there will be no more AI hibernation. On the contrary: the further development and adaptation of AI will be more rapid than the triumphant advance of the smartphone. This will not happen with a big bang. Rather, AI algorithms and applications will quickly find their way into digital services and application software. Therefore, user companies should prepare themselves today for this development, which has already begun. Otherwise they will not be able to realise very good business opportunities in three to five years’ time.
Why is AI so important?
With such a high pressure to act, it is not advisable to wait until more users have gained experience with AI technology in order to carry out a risk-free implementation based on the resulting best practices.
Because AI is not a one-task technology. It is not like the accounting software used by corporate finance departments to manage cash and expenses. AI is already playing a role and will continue to play an increasingly important role in handling a wide range of tasks. It is used wherever decisions have to be made based on data and its patterns. This is more often the case than many people commonly think: facial recognition is based on the comparison of data reference points, just like speech understanding and speech processing. Similarly, examples can be found in the field of predictive maintenance, where stressed components can be replaced shortly before a defect occurs on the basis of comparative data. All these scenarios are now being optimised using AI algorithms. Some of them are already working astonishingly precisely, while others are not yet optimal. Thus, ethical questions for the development and use of AI have not even been answered to any extent. But is it therefore right to wait until all open questions have been clarified?
No, it is not appropriate to classify artificial intelligence processes as overrated emerging technology. The argument that it is better to wait in peace until the technology is mature enough for business use does not hold water with AI. There are many good reasons for this.
The increasing complexity in production, processes and decision parameters, which pushes the existing IT to its limits, speaks against this. Most processes in medium-sized and large companies are IT-supported, and the trend is rising. At the same time, more and more digitally enhanced products and services are coming onto the market. Both dramatically increase the volume of data to be processed. In addition, more and more possibilities are being created for recording and further processing data. According to a rule of thumb, the global volume of data currently doubles in less than two years. The speed at which technologies, products and processes change has also increased enormously in recent years. The term VUCA world is making the rounds; a world characterised by volatility, uncertainty, complexity and ambiguity, i.e. rapid changes, uncertainty, complexity and ambiguity. Classic IT does not cope well with this nix-is-fix model. It reacts too slowly, because it is difficult to adapt, because different programs are difficult to integrate and last but not least, because there is an increasing lack of qualified personnel. Such IT is costly, because own infrastructure and expensive software licences have to be paid and operated. For the same reasons, classic IT is not flexible. When it comes to speed, standardisation and automation help. However, both approaches also make classic IT landscapes extremely inflexible.
Flexibility thanks to intelligent automation
Here, artificial intelligence with clever automation approaches, for example with IoT analytics, test automation or AI security, is to provide relief. In terms of flexibility and costs, cloud computing, software containers and managed cloud services can help. But AI can provide particular support in areas where simple decisions are required. With AI, everyone thinks of granting loans, risk assessments of insurance companies or autonomous driving. That is partly still dreams of the future. But AI has already found its way into the world when it comes to distinguishing perfect from defective components, for example, in translations, in speech recognition and processing, in searches and recommendations on the web, in the navigation systems we all use every day. The digital language assistants Alexa, Siri, Cortana or the Google assistant are brimming with AI. Amazon’s shopping experience would be unthinkable without AI, and the many merchants on the platform are also already intensively supported with AI without them even noticing.
AI sets growth incentives
Another good reason for not waiting is that many market researchers and management consultants expect AI to have an enormous impact on business productivity and on the growth of the world’s economic product. Accenture, for example, estimates that in 2035, AI can generate additional growth of around 1 trillion euros in Germany alone. A prerequisite for this is a far-reaching acceptance of artificial intelligence. For companies that want to participate in this growth, this means that they will have to take care of AI in their processes as well as in their products and services very quickly and intensively. Even the first reports on the benefits of AI suggest that Accenture’s figures are no speculation: In the IT security sector, in a survey conducted by Market Cube on behalf of security provider Cylance, 77 per cent of respondents said they had prevented data attacks more often with AI-supported security tools than without. 81 per cent even said that they had discovered threats before their security teams with AI. This is a good example to demonstrate growth and productivity gains and that it is worth taking a closer look at AI.
Many algorithms have grown out of their infancy
Especially since the common AI algorithms partly originate from the 80s, i.e. they are not untested. Today’s processors, storage systems, connectivity in the gigabit range as well as data storage systems (Data Lakes, NoSQL, in-memory databases, Hadoop, Spark) provide the performance that AI algorithms need to function quickly. This in turn means that many algorithms have long outgrown their infancy, are often open source and therefore available free of license fees. This accelerates development enormously. As a result, AI will become available to a very large number of companies in a short time. Those who do not use it will quickly lose touch. However, it should be clear that standard AI algorithms usually only solve standard challenges. In the business context, many individually developed AI algorithms are needed in addition to these standards.
And: With the increasing spread of artificial intelligence, the demands of customers are growing. They are always oriented towards what is high-quality, convenient and inexpensive. Companies that use AI in their product and service range offer them a better customer experience; market participants who refuse to use these technologies quickly fall behind.
Make data volumes manageable – develop fields of application
Another reason to abandon the reluctance to use AI is the amount of data that is exploding. To analyse and use it in a really exhaustive and fast way only works with the help of AI. Accordingly, expenditure on this is growing correspondingly strongly in companies. IDC market researchers predict that AI spending will rise to $79.2 billion by 2022, which corresponds to an average annual growth rate of 38 percent from 2018 to 2022. Retailers will spend $5.9 billion over the next four years on solutions for automated customer service agents, shopping advisors and product referrals. Also among the top 5 industries by spend are discrete manufacturers, healthcare and process manufacturers. According to IDC, spending will increase most rapidly in federal, personal and consumer services and education through 2022. Most of the money will be spent on service bots, sales recommendations and sales force automation, and automated threat intelligence and prevention. In addition, the areas of predictive maintenance, diagnostic and treatment systems, fraud analysis and detection, intelligent process automation and intelligent consultants and recommendation systems are also showing strong growth.
The application scenarios of AI are diverse, and the growth potential of new technologies is huge. Particularly as they make a decisive contribution to maintaining an overview and mastering the exponentially increasing data growth. All these are important reasons for companies to rapidly expand their AI capabilities. The associated dynamics are enormous and it is important not to miss the boat. One thing is certain: AI will become established faster than smartphones have been able to do.
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