An innovation practice starts with a leader who can articulate the tangible value to the organization by cultivating key relationships, developing resiliency and understanding the financials, strategies, markets, products and consumers of the products and/or services.
From around every corner, from behind every door and through every window our lives are being disrupted by artificial intelligence with embedded machine learning. The escalation and widespread global availability of AI/ML solutions in every possible emergent embryotic product has triggered it as the 'top of mind' blueprint with the majority of global corporate executives with many retail and healthcare Executives as early adopters.
As it entered the 21st century, Amway found that the new gig economy had brought with it an entirely new host of competitors and that the nature of the market itself was shifting as consumers increasingly engaged digitally. Its transformational journey offers essential lessons for enterprise leaders everywhere who are facing disruptive threats and need a roadmap to respond.
AI and machine learning are predicted to be the most positive disrupting technology for banking with an estimated cost saving of more than $1 trillion by 2030. Although AI/ML fits into the “do more with less” mentality and the hope is that chatbot functions will personalize service meeting customer needs faster and more efficiently, it has fallen short so far.
For all too long, Silicon Valley has operated under the laissez-faire notion that the world is just one big beta-test and that conventional rules don’t apply. Finally, a prominent member of the community is calling for change.
We are seeing work split into two broad camps: those that build and support technology, and those that do work that technology cannot (or which we, as a society, are not yet prepared to) automate. As this shift takes root, enterprise leaders will need to understand its impact, and the changes it will require in how they approach sourcing strategies, how they train employees and where and how they invest around the world as we enter what I call the New Human Age.
It's no secret that large organizations are at risk of being disrupted by smaller, more nimble competitors. Transformation-minded CIOs should seize this opportunity and create conditions for innovation to thrive.
The World Economic Forum has brought together the most influential scientists, economists and entrepreneurs to deliberate on the positive and negative aspects of our digital future living and being in what we collectively are calling the age of the 4th Industrial Revolution. Although AI and ML have many positive applications, there are those who fear losing their privacy to AI/ML’s invasiveness, to governments implementing AI/ML seeking economic domination, to organized crime cyber-thieves seeking financial gain or to the lawyers who too seek financial gain from AI/ML oversite and pervasiveness.
In 2015, the UN Member States adopted a 2030 Sustainable Global Agenda. 17 aggressive objectives were recognized, of which the elimination of poverty was at the top. Since the SGA was created, ongoing gatherings of some of the foremost global AI and ML experts, decision-makers and pacesetters in universities, governments, businesses and communities have united in collaboration to find a way to eradicate poverty.
US law enforcement believes they can and will be able to predict future crime events, proactively diffuse possible violent and criminal hotspots ahead of an actual criminal occurrence. Although in its infancy within law enforcement, AI/ML for crime detection, predication and forensic analysis are revolutionizing fast to protect the supply chain and possibly save lives.
Experimentation with Voice Recognition Systems has been a focus since the 1950s and with Defense Advanced Research Projects Agency’s (DARPA) new solicitation offer has included more than just identification and classification. Research based on its Grounded Artificial Intelligence Language Acquisition (GAILA) project has a benchmark of human voice identification, interpretation and understanding.
Even for technology veterans, keeping pace with advancements is like chasing a moving train that will always be just a bit faster. Try as you may, you can never quite catch up and, if you stop trying, you will never catch up.
The declining funding rates for early-stage digital health startups is curiously at odds with the burning desire in healthcare enterprises to drive technology-led innovation and accelerate digital transformation.
Deciding whether to buy off-the-shelf AI or build your own AI-based business solutions is a complex equation based on available talent, business needs, desired outcomes, lock-in comfort and a rapidly evolving market.
The commercial moving concern digitized a manual sales process, resulting in reduced administrative overhead and additional revenues. CIO Len O’Neill describes the creation of Suddath’s Estimator software.
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