Decentralizing the operations at organizations, has long been a pipe dream for team strategists. Now, AI may be deployed to finally come to terms with the actual implementation. Satalia is one company that is working towards this scenario. Its CEO, Daniel Hulme predicts a scenario in this company where the workforce can decide its holidays by themselves, and all coordination is done automatically. Instead, AI and open innovation can solve these problems. Such structures are known as swarm organizations. Satalia isn’t a small company. It has a team of about two- hundred and fifty employees, but is able to largely work through a decentralized structure. This model for talent management can actually be deployed to even larger organizations, and ultimately to countries as well.

Source:https://hbr.org/podcast/2020/06/using-ai-to-decentralize-organizations?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert_not_activesubs&deliveryName=DM82910

Uploaded Date:09 June 2020

During times of crises, several companies rise above their pre- crisis levels. This was true for the recession of 2007- 08 and the smaller one earlier in 2000- 01. The present crisis the world is facing will also meet a similar follow- up. Several will rise up as the leaders in their segments. To do that, companies will need to first and foremost, demystify AI. Artificial Intelligence needs to be for all and with all. This is because AI can offer benefits in five broad areas to all kinds of employees. One is in foresight through the use of business analytics. Another is in assistance. Then there is expertise, and also explanation and simulation. Trust worthy AI advocates need to be groomed. The existing business intelligence capabilities need much bolstering. Common grounds need to be highlighted, while the benefits have to be personalized.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-to-build-ai-with-and-for-everyone-in-your-organization

Uploaded Date:29 May 2020

AI systems are here to stay, so it is best that humans make peace with them. An ideal team must be comprised of both machines and humans. In this way, the abilities of both the sides can be better leveraged. Human beings bring empathy and creativity to the table. AI on the other hand, possesses of superior business analytics capabilities. This can break down huge treasure troves of data to extract meaningful and coherent business insights. Intel is one of the most successful organization organizations in this process. They have not reduced their talent recruitment either. They have merely tailored it now to hire more people who are likely to extract the maximum benefits out of AI bots and devices.

Source:https://sloanreview.mit.edu/article/designing-ai-systems-with-human-machine-teams/

Uploaded Date:31 March 2020

By now, it is becoming increasingly evident, on how AI has changed work, and is set to do further. Business leaders too need to adapt to this new scenario. Job generation may slow down as confirmed by more than half the respondents in a survey conducted on Harvard Business School alumni. There are various ways to take on this paradigm shift. One is to reallocate the capital resources towards more online jobs. The proof in the pudding for its viability is the business research carried out by the MIT- IBM Watson AI Lab. This found over one- hundred and seventy million online jobs for the period between 2010 and 2017. Greater investment needs to be carried out toward management training of the employees. This education and skilling needs to start from today itself, in order to bear fruit sometime in the future.

Source:https://hbr.org/2020/03/ai-is-changing-work-and-leaders-need-to-adapt?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert_activesubs&utm_content=signinnudge&referral=00563&deliveryName=DM73877

Uploaded Date:31 March 2020

Beyond the technology alone, the success or failure of any Machine Learning (ML) initiative depends on its scalability. ML has also initiated a kind of move away from the conventional sequential mode of thinking. In order to ensure scalability, companies are using a certain metric called TOPS or Trillions of Operation Per Second. Getting the right inference post the business analytics functions performed using ML, also involves the use of multiple variables. These too need to be verified. The architecture adopted too needs to be flexible and heterogeneous. Project Trillium is one such being worked by Arm exploring the growth of ML. Arm has been one of the best in terms of scaling up.

Source:https://www.technologyreview.com/s/614660/the-success-of-machine-learning-rests-on-scalability/

Uploaded Date: 16th December 2019

In order the gauge the overall value of AI, and how to succeed with it in business, a recent study was anchored by the MIT along with SMR and management consulting giant BCG. One of the key findings is to integrate the AI strategies with the broader business strategies. Production of AI needs to be linked to its consumption. The talent recruitment systems must also be geared up towards hiring of personnel in data science, AI technology and processes. The difficulties in implementation need be addressed. This will help manage the risks. Opportunities may also then be spotted, so they may be duly exploited. AI has to be a part of the holistic digital initiatives taken by the company. Revenue aims must be spelt out, right at the outset. As much as it may seem contrarian, AI may actually turn in to a force for unification. This is through applying universal norms across data streams throughout an organization.

Source:https://sloanreview.mit.edu/projects/winning-with-ai/

Uploaded Date:28 October 2019

Artificial Intelligence (AI) is here, and very much to stay. Business’ expectations though have now risen to sky- high proportions, leading to unrealistic an understanding. The MIT Sloan Management Review, in collaboration with the Boston Consulting group, produced an extensive report highlighting, how AI is presently being deployed across organizations. The report also states the various steps the top executives need to undertake, in order to maximize the benefits out of the same. What has been observed is a growing gap between the execution of the projects with the goals set. The vast majority of company heads believe that AI will give them a competitive edge over their competitors. However, less than two- fifths of those surveyed, currently have a proper AI strategy. Instead, they have been improvising data- driven business analytics they end up conducting. There is also a serious dearth in professionals who can conduct corporate training sessions around AI. Leaders need to themselves have a deeper understanding, plus support is needed from the very top.

Source:https://sloanreview.mit.edu/projects/reshaping-business-with-artificial-intelligence/

Uploaded Date:14 October 2019

HR has not historically been known for nurturing the most cutting- edge of technologies. Yet, a massive opportunity presents itself now in the form of Artificial Intelligence (AI). As the workforce enters the year 2020, there are a few trends that are already being identified, taking place in HR, as a result of AI’s intrusion. For a start, in the field of talent recruitment, AI combined with human intelligence, is bringing about an enhancement to the candidate’s experience. Skills that are uniquely human, such as emotional intelligence and technology design will prosper, as per the World Economic Forum (WEF). Newer jobs will be created where AI will be used, as already there are so many that didn’t exist barely a decade back. The AI ready workforce will also prove to be crucial to any organization’s future. Hiring will depend a lot on the skills available, rather than mere qualifications. Corporate training is already being transformed due to the deployment of Virtual Reality (VR). Beyond money, a lot of workers will seek meaning at work.

Source:https://www.entrepreneur.com/article/337164

Uploaded Date:11 September 2019

The term Machine Learning (ML) is much in use now, but few understand it for exactly what it is. Ultimately ML is something that uses statistics to find patterns across huge quantities of data warehousing done. Some key digital- era giants such as Facebook, Twitter, Netflix, Baidu, Google and YouTube are all at the forefront of this. Social media companies and search engines use this data to mobilize their digital marketing efforts, even using voice assistants in the process. It all owes to an invention dating back to the year 1986, by Geoffrey Hinton. The related field is called deep learning, but this one goes even more to the depths, and in much quicker time. Neural networks work similar to how the human brain is wired. This ML comes in three major forms. These are known as supervised, unsupervised and reinforcement learning.

Source:https://www.technologyreview.com/s/612437/what-is-machine-learning-we-drew-you-another-flowchart/

Uploaded Date:03 July 2019

The general understanding is that while the rise of Artificial Intelligence (AI) will cause a lot of jobs loss, it will also generate new ones. Corporate leaders must now be thinking what to do next to engage with this trend. One area in which people will need to work on will be soft skills. The frequency of management training sessions will need to be increased in order to equip employees with these skills. These will be necessary to collaborate with smart machines. Soft skills includes a whole host of skills such as social and emotional intelligence, creativity, sensory perception and complex reasoning. Responsible AI will thus mark a new frontier. Shifts in learning will now need to be accommodated for training the existing personnel.

Source:https://sloanreview.mit.edu/article/revisiting-the-jobs-artificial-intelligence-will-create/

Uploaded Date:26 June 2019

A professor from the Toronto- based Rotman School of Management has explained the economics and the subsequent impact of Artificial Intelligence (AI). Professor Ajay Agrawal, besides training the MBA students, also works with several startups from the field at the Creative Destruction Lab. He has written a new book, titled Prediction Machines: The Simple Economics of Artificial Intelligence, co- authored by fellow academicians. To harness the true powers of AI, the book says that a time- frame has to be worked out, within which the operations will be put in to place. The progress once started, will be exponential. The machines need be trusted. Before conducting any business analytics operation, based on the data available, one needs to know the requirements. The company must know what kind of insights are desired. A kind of learning loop must be created, making it easier for all team members to obtain the relevant information. Data, judgment and action and further growing in importance.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-economics-of-artificial-intelligence

Uploaded Date:26 June 2019