Those with the HR teams, training program, organizational structures, and adaptable staff will be best prepared for this fast-approaching reality.
Artificial Intelligence is already forcing leadership teams around the world to reconsider some of their core structures. Fundamentally. organizations need an AI Strategy to stay completive
Deloitte’s 2017 Human Capital Trends Report, draws on surveys from over 10,000 HR and business leaders in 140 countries.
Most of the changes are a result of the early penetration of basic AI and the preparation organizational need to do as AI emerges and matures.
Advances in technology and AI or now proven to result in:
“AI is definitely not eliminating jobs,
it is eliminating tasks of jobs, and creating new jobs.”
“The new jobs that are being created are more human jobs”
“Individuals that have very task-oriented jobs will have to be retrained, or they’re going to have to move into new roles”
Josh Bersin, Principal and Founder of Bersin by Deloitte
‘More Human Jobs’ require traits robots haven’t yet mastered, like empathy, communication, and interdisciplinary problem solving. “
The Deloitte survey also found that
Early AI technologies and a looming AI revolution are forcing organizations to reevaluate established strategies.
The integration of artificial intelligence tools is transforming organizations to become more collaborative and team-oriented, as opposed to the traditional top-down hierarchal structures.
“To integrate AI, you have to have an internal team of expert product people and engineers that know its application and are working very closely with the frontline teams that are actually delivering services.”
“When we are working AI into our frontline service, we don’t go away to a dark room and come back after a year with our masterpiece.
We work with our frontline day in, day out.”
Ian Crosby, Co-Founder and CEO of Bench (a digital bookkeeping provider)
organizations are moving away from a top-down structure and toward multidisciplinary teams to adapt to changing technologies.
Finding a balanced team structure, however, doesn’t happen overnight, explains Crosby. “Very often, if there’s a big organization, it’s better to start with a small team first, and let them evolve and scale up, rather than try to introduce the whole company all at once.”
Beyond checking the boxes of the job’s technical requirements, organizations are now looking for candidates that are ready to adapt to the changes that are coming.
“When you’re working with AI, you’re building things that nobody has ever built before, and nobody knows how that will look yet,” he says. “If they’re not open to being completely wrong, and having the humility to say they were wrong, we need to reevaluate.”
As AI becomes more sophisticated, leaders will eventually need to decide where to place human employees, which tasks are best suited for machines, and which can be done most efficiently by combining the two.
“It’s a few years before we have actual AI, it’s getting closer and closer, but AI still has a big problem understanding human intent.”
Rurik Bradbury, LivePerson’s Global Head of Research and Communication.
As more AI software becomes available, organizations must think of new hires in three different categories
Recently many organizations have deployed Artificial Intelligence (AI), which has included neural networks, expert systems and voice-recognition systems.
Managers and developers understand very little about how management and organizations affect or are affected by the technology.
Using specific examples from practice and research, the interaction of AI, management and organizations is presented.
Some of the effects of AI on organizations include:
The possibility of power shifts within an organization because of changes in the ownership and control of knowledge is inevitable
AI is emerging as our most powerful ally for cybersecurity, especially as it has become clear that relying primarily on humans to fight this war is a losing battle plan.
Cybercriminals have created one of the largest illegal economies in the world, generating $445 billion in annual profits and stealing more than a billion records of personal information, such as credit card numbers and health records, every year.
The most concerning fact, though, is that 80 percent of cyberattacks are driven by highly organized crime rings that freely exchange data, tools, and tricks of the trade. Cybersecurity experts just can’t keep up, and the situation will continue to be challenging with a projected 1.5 million security jobs to remain unfilled between now and the conclusion of this decade.
Cybersecurity experts need technology that augments their abilities by filling gaps in monitoring and identifying threats.
There is a growing understanding among security experts about the benefits of cognitive security. A recent survey by the IBM Institute of Business Value found that nearly 60 percent of security professionals believe cognitive security solutions can significantly slow down cybercriminals.
The same survey revealed there will be a threefold increase in the percentage of companies implementing cognitive-enabled security solutions in the next two to three years, from 7 to 21 percent. This won’t alleviate the need to hire additional cybersecurity experts, however, because the fight against cybercrime will require a closer alliance between human and machine.
Humans face a staggering volume of data and humans alone simply can’t consume all of it. The average organization sees over 200,000 pieces of security event data per day, with enterprises spending $1.3 million a year dealing with false positives alone, equaling nearly 21,000 wasted hours.
AI will help security professionals by sorting through all this data, using natural language processing to understand the imprecise human language contained in blogs, articles, videos, reports, alerts, and other unstructured data; connecting obscure data points humans couldn’t possibly spot; and making recommendations on remediation strategies based on those connections and insights.
Without AI, unstructured data will continue to be the Achilles heel of cyberdefense because it represents a huge blind spot, comprising more than 80 percent of all data.
Augmenting the expertise of cyber professionals, AI systems are learning how to monitor unstructured data to detect risks before they emerge. As they continue to learn, AI systems will be more adept at detecting the difference between a computer glitch and a malicious attack, alleviating the need for security analysts to waste their valuable time on wild goose chases.
Once an attack is identified, security analysts often turn to the internet for the latest ways to address it, generating thousands of pages of results that may or may not contain the solution. It’s a process that is neither fast nor accurate. In this stage of the fight, AI can play an important role analyzing reams of information, including unstructured data, to identify the most probable fixes — and do so in orders of magnitude faster than any human.
While we are just on the forefront of the cognitive era of security, progress is well underway in making this vision a reality. Cognitive tools such as IBM’s Watson are currently being trained to ingest and understand vast amounts of security data and research created for human consumption. Dozens of organizations are already working with this technology and helping discover new ways Watson can be used in the fight against cybercrime.
In the future, bots will seek out network vulnerabilities, diagnose them, and recommend ways to patch them — all while working seamlessly with cybersecurity experts, who will be even more valuable in the fight against cybercrime because they have been trained in the use of augmented intelligence.
Today, the often-automatic reaction to any mention of systems gaining intelligence is that the robots have come to take our jobs. In the war on cybercrime, reality could not be further from this view. AI will enable humans to deal with ever-increasing threats by augmenting our expertise — but it’s critical for people to first understand and accept the true definition of AI.
Individuals and societies will be forced to deal with the disruptive threat of AI. Billionaire Elon Musk has a suggestion of how to avoid becoming irrelevant as Artificial Intelligence (AI) becomes more present in our work and personal lives.
The Tesla and SpaceX CEO said recently “that humans need to merge with machines to become a sort of cyborg.” Musk made these assertions recently at the World Government Summit in Dubai.
Elon Musk speculates that we will see a new layer of a brain able to access information quickly and tap into artificial intelligence.
"Over time I think we will probably see a closer merger of biological intelligence and digital intelligence"
"It's mostly about the bandwidth, the speed of the connection between your brain and the digital version of yourself, particularly output."
Elon Musk told an audience at the World Government Summit in Dubai, where he also launched Tesla in the United Arab Emirates (UAE).
Musk explained what he meant by saying that computers can communicate at "a trillion bits per second", while humans, whose main communication method is typing with their fingers via a mobile device, can do about 10 bits per second.
In an age when AI threatens to become widespread, humans would become useless, so there's a need to merge with machines, according to Musk.
"Some high bandwidth interface to the brain will be something that helps achieve a symbiosis between human and machine intelligence and maybe solves the control problem and the usefulness problem."
The more immediate threat is how AI, particularly autonomous cars that will displace jobs.
In the 2010s AI is starting to have an impact to our job security.
Musk predicts that in the next 20 years, 12 to 15 percent of the global workforce will be unemployed because of the impact of AI.
Musk touched upon his fear of "Deep AI" which goes beyond driverless cars to what he called "artificial general intelligence". Deep AI is "smarter than the smartest human on earth" and Musk called this a future "dangerous situation".
The precise cause of this change is the imminent creation by technology of entities with greater than human intelligence.
This breakthrough will be achieved through:
What are the consequences of this event? When greater-than-human intelligence drives progress, that progress will be much more rapid.
The singularity is a point where our models must be discarded and a new reality rules. As we move closer to this point, it will loom large over human affairs until the notion becomes commonplace.
One conversation centered on the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.
A Research Perspective: Artificial Intelligence, Management and Organizations, Intelligent Systems in Accounting, Finance, and Management, 1993.
Deloitte’s 2017 Human Capital Trends Report, Deloitte University Press, 2017.
Elon Musk: Humans must merge with machines or become irrelevant in AI age, CBC.com, 13 Feb 2017 .http://www.cnbc.com/2017/02/13/elon-musk-humans-merge-machines-cyborg-artificial-intelligence-robots.html
The Coming Technological Singularity: How to Survive in the Post-Human Era, Vernor Vinge, Department of Mathematical Sciences San, Diego State University, 1993.
Why AI must be redefined as ‘augmented intelligence’, Venturebeat, January 9, 2017.