 artificial intelligence for all responsibly artificial intelligence for all responsibly hemraj fri 10172025 250 artificial intelligence for all responsibly contributors jeff lanham linkedin artificial intelligence for all responsibly jeff lanham ai value realization latest trending image artificial intelligence for all responsibly as we look towards the turn of another year it is a time of introspection for many organizations annual forecasting budgeting and planning efforts are likely in progress by now often bringing increased stress and anxiety to the csuite and the managers that report to them everyone is asked to predict the future based on entirely insufficient information no one knows what will happen so there are usually no alternatives to good oldfashioned guessing sure you can build a spreadsheet do elaborate calculations and ultimately convince yourself that your forecasts are spoton still overwhelming research shows human judgement is prone to error bias and noise so how do you make the best guesses you can what tools and technologies can help you guess better enter artificial intelligence ai the availability of virtually unlimited and relatively inexpensive compute and storage capabilities in the cloud today along with advances in both the capabilities and usability of ai software offer unprecedented opportunities to crunch the numbers in new and different ways we are now well past the point where computers are more effective than people at many databased tasks including searching extrapolating interpolating predicting and even winning strategy and video games in other words computers have gotten much better at guessing and making judgements than we are in the nottoodistant past designing building testing and delivering working solutions based on artificial intelligence and machine learning ai ml was complicated and expensive fortunately stateoftheart ai ml technology has been evolving rapidly over the last few years and several major vendors now offer powerful tools and capabilities at price points that are reasonable for nearly all organizations in fact according to deloitte s state of ai in the enterprise survey for the 2022 edition 94 of the 2600 business leaders surveyed agree that ai is critical to success over the next five years a recent accenture survey of over 1600 csuite executives and datascience leaders from the world s largest organizations found that nearly 75 of companies have integrated ai into their business strategies and reworked their cloud plans to achieve ai success while adoption does remain somewhat higher in the enterprise space a recent report from mckinsey showed that 56 of all respondents report ai adoption in at least one function microsoft is one of the leaders in data science and management and has invested heavily for years in expanding ai ml capabilities across many of its products and platforms the microsoft azure cloud offers various services and tools that make it relatively easy to create robust ai ml solutions for many scenarios microsoft has taken the integration of these technologies with core products to a new level with the recent introduction of syntex which brings content ai into sharepoint it enables productivityboosting functionality including automatic document recognition classification summarization translation automated content generation automated document assembly aipowered search and active dynamic security compliance resilience in addition to aibased content processing there are a lot of other potentially compelling scenarios for many types of organizations regardless of size industry business type etc some of the most common examples of successful ai ml outcomes include the following  general decision support  predict likely effects of various options interpreting unstructured content  search identification organization reuse automated document classification  assign content types security levels etc auditing compliance ediscovery  understand what you have where it is how it is used resume analysis  interpret and rate candidates based on machine learning anomaly detection  identify outliers unexpected results and process bottlenecks customer churn reduction  identify atrisk customers in time to take corrective action support process optimization  analyze support tickets response resolution times issue types language processing  interpret and translate between languages natural language queries image recognition and classification  identify and tag pictures and graphics audio and video transcription  turn sounds and images into text content generation  create content and media based on similar existing items texttospeech however all the magic that ai might seem to promise has a critical caveat along with the exciting possibilities that ai ml offers it is essential not to lose sight of the potential risks that can arise if care is not taken in implementing solutions artificial intelligence can deliver substantial benefits to organizations that successfully leverage its power but if executed without attention to ethical legal and other peoplecentric and societal considerations ai could also cause significant or even calamitous damage to a company s reputation and prospects to ensure maximum value while minimizing the corresponding risks it is helpful to have a frame of reference to assess ai technologies in that spirit deloitte has developed a valuable paradigm for evaluating aibased solutions the six dimensions in the trustworthy ai framework are  fair and impartial  help participants understand how their data can be used and how ai systems make decisions algorithms attributes and correlations are open to inspection transparent and explainable  assess whether ai systems include internal and external checks to help enable equitable application across all participants responsible and accountable  put an organizational structure and policies in place that can help determine who is responsible for the output of ai system decisions robust and reliable  confirm that ai systems can learn from humans and other systems and produce consistent and reliable results respectful of privacy  respect data privacy and avoid using ai to leverage customer data beyond its intended and stated use allow customers to opt in and out of sharing their data safe and secure  protect ai systems from potential risks including cyber threats that may cause physical and digital harm whether your business is a fortune 500 firm or a small organization with limited resources there are almost certainly one or more areas where artificial intelligence machine learning solutions could significantly impact the bottom line of course given some recent survey results you can be sure that other organizations in your space are also exploring the big beautiful and slightly scary world of ai ml don t be too late for the party but be careful on your way there  disclaimer copyright 2022 by divihn integration inc  yoursuccess divihncom the creator of the document reserves all rights publication date november 2022 divihn integration inc reserves the right to change the contents of this article the features or the scope without the obligation to notify anyone of such changes the content has been adapted using secondary research from various data points via google search infographics and images used in the document are the property of the respective owners and have been used for indicative purposes only the author reserves the right to authorize and use the intellectual property contained in the document webinar image the ciso exchange for a safer digital world image zero trust architecture adoption in federal government image zero trust architecture adoption in federal government expert content image shadow ai and the governance gap what leaders must do now shantanoo govilkar image security by design part 2 joseph f norton image employee training awareness laszlo s gonc popular articles unleashing business potential the power of adaptive enterprise architecture in the digital age businesses must adopt an ad 15 best practices in salesforce development many businesses have decided to use salesforce  what is governance risk and compliance grc a definitive guide grc is the capability or integrated collection artificial intelligence for all responsibly as we look towards the turn of another year it get the latest insights straight from our desk to your inbox subscribe featured articles explore more  image whitepaper ransomware threat management ransomware continues to be a real threat to business operations across all industries no organization is safe from this threat laszlo s gonc cissp first senior fellow divihn cybersecurity center of excellence view image cybersecurity incident response preparedness an incident response framework provides a structure to support incident response operations a framework typically provides guidance on what needs to be done but not on how it is done laszlo s gonc 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