An artificial intelligence (AI) strategy has become a vital tool every organisation needs. Based on my experience helping companies develop their AI strategies, I share my nine things every AI strategy must include.
Accenture migrated its data platform and over 50 analytics applications to Google Cloud to modernize its capabilities, increase cost efficiency, and enable insights faster. The migration involved moving hundreds of terabytes of data from the legacy system to Google Cloud's scalable architecture while ensuring no downtime. Applications were reimplemented to use cloud-native components and on-demand resources. This transformation reduced administrative overhead, improved cost efficiency through Google Cloud's pay-as-you-go model, and allowed Accenture to leverage other innovative solutions to meet evolving business needs.
Explore how different industries are embracing the utility of AI to create and deliver new value for their customers and organisation
* Discuss the state of maturity of AI across industries
* Get an appreciation of business posture to AI projects
We also review the utility of AI across several industries including:
* Healthcare
* Newsroom & Journalism
* Travel
* Finance
* Supply Chain / eCommerce / Retail
* Streaming & Gaming
* Transportation
* Logistics
* Manufacturing
* Agriculture
* Defense & Cybersecurity
Part of the What Matters in AI series as published on www.andremuscat.com
[Note: This is a partial preview. To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a collection of PowerPoint diagrams and templates used to convey 20 different digital transformation frameworks and models.
INCLUDED FRAMEWORKS/MODELS:
1. Ten Guiding Principles of Digital Transformation
2. The BCG Strategy Palette
3. Digital Value Chain Model
4. Four Levels of Digital Maturity
5. Customer Experience Matrix
6. Design Thinking Framework
7. Business Model Canvas
8. Customer Journey Map
9. OECD Digital Government Transformation Framework
10. Accenture's Nonstop Customer Experience Model
11. MIT's Digital Transformation Framework
12. McKinsey's Digital Transformation Framework
13. Capgemini's Digital Transformation Framework
14. DXC Technology's Digital Transformation Framework
15. Gartner's Digital Transformation Framework
16. Cognizant's Digital Transformation Framework
17. PwC's Digital Transformation Framework
18. Ionolgy's Digital Transformation Framework
19. Accenture's Digital Business Strategy Framework
20. Deloitte's Digital Industrial Transformation Framework
Artificial intelligence is reshaping business, and the time is ripe for companies to capitalise AI. The organisation can use AI to move their focus from discrete business problems to significant business challenges.
An organisation should use ML and Data Science to drive digital transformation for more back-office operational efficiency, better user/engagement, smoother onboarding, and better ROI by lowering cost and bring more data-driven taking mechanism for transparency.
AI will be a valuable, transformational change agent not only to the way business is done but to the way people live their daily lives if it isn't perceived as a plug-and-play technology with immediate returns but more like a long term solution to rewire the organisation.
AI will significantly change how PR and marketing professionals work in 2024 according to predictions from Golin's global experts:
1) AI will enable brands to increase social media posting frequencies and generate new types of content at faster speeds.
2) AI tools will optimize content based on objective performance data rather than subjective feedback, removing the guessing game.
3) PR professionals will need to ensure AI systems are trained on accurate, positive information about companies to influence how information is delivered.
Generative AI Use cases for Enterprise - Second Session
This document provides an overview of generative AI use cases for enterprises. It begins with addressing concerns that generative AI will replace jobs. The presentation then defines generative AI as AI that generates new content like text, images or code based on patterns learned from training data.
Several examples of generative AI outputs are shown including code, text, images and advice. Potential use cases for enterprises are then outlined, including synthetic data generation, code generation, code quality checks, customer service, and data analysis. The presentation concludes by emphasizing that people will be "replaced by someone who knows how to use AI", not AI itself.
Digital Reference Architecture- A FOCUS ON MIDDLEWARE “THE KILLER APP”
Understand the importance of having the Integration Strategy, Roadmap and Architecture that will drive and meet the Enterprise Digital Transformation goals and objectives.
The STATT (Strategic Technical Application Techniques and Tactics) methodology from Kellton Tech helps your organization to successfully lay down a Digital Reference Architecture that addresses
Digital Transformation Strategy and Roadmap
High-Speed IT of Digital Systems through DevOps
Multi-Speed IT Integration and Connectivity Architecture through CI/CD
Bi-Modal IT Considerations for Digital Innovation
Digital Reference Architecture Process, Methodology and Outcomes
Digital IT Trends - API based Connectivity, Structured and Unstructured Big Data Analytics, Micro-services and more
Ron Tolido presented this at our Meetup on Sept. 16th, 2013.
With digital transformation, the use of digital technologies to radically improve the performance or reach of enterprises, companies can become more customer-centric, more valuable and more profitable. Ron Tolido (@rtolido) discusses digital maturity, digital governance and the role of the chief digital officer (CDO), design principles and a digital transformation roadmap.
Big data and artificial intelligence have developed through an iterative process where increased data leads to improved infrastructure which then enables the collection of even more data. This virtuous cycle began with the rise of the internet and web data in the 1990s. Modern frameworks like Hadoop and algorithms like MapReduce established the infrastructure needed to analyze large, distributed datasets and fuel machine learning applications. Deep learning techniques are now widely used for tasks involving images, text, video and other complex data types, with many companies seeking to gain advantages by leveraging proprietary datasets.
In this webinar Seth Earley establishes the formula for AI success, demystifies the topic for executives and provides actionable advice for data strategists.
Key Takeaways:
**AI-Powered solutions begin with a focus on business goals
**Successful AI requires a semantic data layer built on a solid enterprise information architecture.
**Instrumenting measuring ROI should be part of every AI program
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
Accenture migrated its data platform and over 50 analytics applications to Google Cloud to modernize its capabilities, increase cost efficiency, and enable insights faster. The migration involved moving hundreds of terabytes of data from the legacy system to Google Cloud's scalable architecture while ensuring no downtime. Applications were reimplemented to use cloud-native components and on-demand resources. This transformation reduced administrative overhead, improved cost efficiency through Google Cloud's pay-as-you-go model, and allowed Accenture to leverage other innovative solutions to meet evolving business needs.
Explore how different industries are embracing the utility of AI to create and deliver new value for their customers and organisation
* Discuss the state of maturity of AI across industries
* Get an appreciation of business posture to AI projects
We also review the utility of AI across several industries including:
* Healthcare
* Newsroom & Journalism
* Travel
* Finance
* Supply Chain / eCommerce / Retail
* Streaming & Gaming
* Transportation
* Logistics
* Manufacturing
* Agriculture
* Defense & Cybersecurity
Part of the What Matters in AI series as published on www.andremuscat.com
[Note: This is a partial preview. To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a collection of PowerPoint diagrams and templates used to convey 20 different digital transformation frameworks and models.
INCLUDED FRAMEWORKS/MODELS:
1. Ten Guiding Principles of Digital Transformation
2. The BCG Strategy Palette
3. Digital Value Chain Model
4. Four Levels of Digital Maturity
5. Customer Experience Matrix
6. Design Thinking Framework
7. Business Model Canvas
8. Customer Journey Map
9. OECD Digital Government Transformation Framework
10. Accenture's Nonstop Customer Experience Model
11. MIT's Digital Transformation Framework
12. McKinsey's Digital Transformation Framework
13. Capgemini's Digital Transformation Framework
14. DXC Technology's Digital Transformation Framework
15. Gartner's Digital Transformation Framework
16. Cognizant's Digital Transformation Framework
17. PwC's Digital Transformation Framework
18. Ionolgy's Digital Transformation Framework
19. Accenture's Digital Business Strategy Framework
20. Deloitte's Digital Industrial Transformation Framework
Artificial intelligence is reshaping business, and the time is ripe for companies to capitalise AI. The organisation can use AI to move their focus from discrete business problems to significant business challenges.
An organisation should use ML and Data Science to drive digital transformation for more back-office operational efficiency, better user/engagement, smoother onboarding, and better ROI by lowering cost and bring more data-driven taking mechanism for transparency.
AI will be a valuable, transformational change agent not only to the way business is done but to the way people live their daily lives if it isn't perceived as a plug-and-play technology with immediate returns but more like a long term solution to rewire the organisation.
AI will significantly change how PR and marketing professionals work in 2024 according to predictions from Golin's global experts:
1) AI will enable brands to increase social media posting frequencies and generate new types of content at faster speeds.
2) AI tools will optimize content based on objective performance data rather than subjective feedback, removing the guessing game.
3) PR professionals will need to ensure AI systems are trained on accurate, positive information about companies to influence how information is delivered.
Generative AI Use cases for Enterprise - Second SessionGene Leybzon
This document provides an overview of generative AI use cases for enterprises. It begins with addressing concerns that generative AI will replace jobs. The presentation then defines generative AI as AI that generates new content like text, images or code based on patterns learned from training data.
Several examples of generative AI outputs are shown including code, text, images and advice. Potential use cases for enterprises are then outlined, including synthetic data generation, code generation, code quality checks, customer service, and data analysis. The presentation concludes by emphasizing that people will be "replaced by someone who knows how to use AI", not AI itself.
Understand the importance of having the Integration Strategy, Roadmap and Architecture that will drive and meet the Enterprise Digital Transformation goals and objectives.
The STATT (Strategic Technical Application Techniques and Tactics) methodology from Kellton Tech helps your organization to successfully lay down a Digital Reference Architecture that addresses
Digital Transformation Strategy and Roadmap
High-Speed IT of Digital Systems through DevOps
Multi-Speed IT Integration and Connectivity Architecture through CI/CD
Bi-Modal IT Considerations for Digital Innovation
Digital Reference Architecture Process, Methodology and Outcomes
Digital IT Trends - API based Connectivity, Structured and Unstructured Big Data Analytics, Micro-services and more
Ron Tolido presented this at our Meetup on Sept. 16th, 2013.
With digital transformation, the use of digital technologies to radically improve the performance or reach of enterprises, companies can become more customer-centric, more valuable and more profitable. Ron Tolido (@rtolido) discusses digital maturity, digital governance and the role of the chief digital officer (CDO), design principles and a digital transformation roadmap.
This document provides an introduction and overview of data science. It discusses Ravishankar Rajagopalan's educational and professional background working in data science. It then covers various topics related to data science including common applications, required skills, the typical project lifecycle, team aspects, career progression, interviews, and resources for learning. Examples of unusual real-world applications are also summarized, such as using machine learning to optimize inventory levels for an oil and gas company and implementing speech recognition to predict customer intent for a call center.
The Industrialist: Trends & Innovations - February 2023accenture
The document provides an overview of recent innovations in industrial technology, including Hyundai Mobis' development of gesture control for vehicle infotainment displays, Bosch and IBM's partnership to advance material science using quantum computing, Valmet's intelligent and sustainable valve controller, and Hyundai E&C's quadruped robot for construction site monitoring. It also summarizes projects from companies like ICON, ExxonMobil, Caterpillar, and PORR that are developing more sustainable technologies and materials for applications in industries like construction, mining, and carbon capture.
The 7 Biggest Artificial Intelligence (AI) Trends In 2022Bernard Marr
The document discusses 8 major artificial intelligence trends for 2022:
1. The augmented workforce, where AI tools will help boost workers' abilities and make jobs more efficient.
2. Bigger and better language models that can generate more human-like text.
3. Increased use of AI in cybersecurity to detect network threats.
4. Role of AI in developing virtual worlds known as the "metaverse."
5. Growth of low-code and no-code tools that make AI development simpler.
6. Advancements in autonomous vehicles like cars and ships.
7. AI that can generate more complex creative works like art and music.
8. Continued pushing of boundaries in what AI systems
Artificial intelligence transforming the phase of supply chain managementRahul R
Artificial intelligence is transforming supply chain management by optimizing business processes and establishing agile supply chains. AI can help with inventory control and planning by accessing real-time information on customer demands and inventory levels. It can also help with transportation network design challenges like routing and scheduling through techniques like genetic algorithms and ant colony optimization. Expert systems allow purchasing managers to evaluate suppliers and make more informed make-or-buy decisions. Overall, integrating AI offers competitive advantages through predictive analytics and more efficient supply chain management.
Learn to identify use cases for machine learning (ML), acquire best practices to frame problems in a way that key stakeholders and senior management can understand and support, and help create the right conditions for delivering successful ML-based solutions to your business.
3 Important Ways Artificial Intelligence Will Transform Your Business And Tur...Bernard Marr
Artificial Intelligence (AI) is likely to be the most powerful technology humans have ever had access to. Here we look at the three main ways AI can be used in businesses to deliver success
How To Identify The Data Opportunities For Every Business?Bernard Marr
Today, what differentiates a market-leading company from an also-ran is often the way that it is using data. Data is often referred to as “the oil of the information age” as it powers revolutionary concepts such as artificial intelligence (AI) and the
Why Is Data Literacy Important For Any Business?Bernard Marr
The more data literate your organisation is, the better your results will be. In my work with companies all over the world, I see it every day that organisations that fail to boost data literacy of their employees will be left behind because they are not be able to fully use the vital business resource of data to their business advantage. In this post, I explore what data literacy is, why it's crucial for every business and ways to promote data literacy.
10 Business Functions That Are Ready To Use Artificial IntelligenceBernard Marr
Artificial intelligence (AI) and machine learning are starting to be adopted by businesses across nearly every industry even though it's still a new technology, and there's no way of knowing all that it will enable us to do once it's matured. Here are 10 business functions that are ready to use artificial intelligence.
Overcoming AI Challenges with IBM’s AI LadderBernard Marr
With $16 trillion up for grabs by 2030, there’s a race to be leaders and pioneers in the brave new world of AI and automation. Across every industry, we see an acceleration in the rollout of smart, cognitive systems that promise improved customer experience and streamlined more efficient business processes.
Job Search In The Age Of Artificial Intelligence - 5 Practical TipsBernard Marr
Artificial intelligence is altering how individuals search for a job and how organizations recruit and assess a candidate’s skill-set and credentials for open positions. Here are some practical tips candidates must know in order to get through AI-powered screening in their job search.
What Is Unstructured Data And Why Is It So Important To Businesses?Bernard Marr
Unstructured data is created at an incredible rate each day and with the advent of artificial intelligence and machine learning tools to gather, process, analyse and report insights from unstructured data, it now provides important business value to organizations. It’s essential for all businesses to start making the most of their unstructured data.
Jair Ribeiro - Defining a Successful Artificial Intelligence Strategy for you...Codiax
To develop a successful AI strategy, it must be part of an overarching business plan and tied to business priorities and strategic goals. An AI strategy also requires a data strategy to ensure sufficient and relevant data is available for training models. Additionally, ethical and legal issues around privacy, bias, and consent must be considered. Developing AI skills and managing cultural changes are also important to successfully implement an AI strategy.
The document discusses how companies can leverage data and analytics to gain competitive advantages. It notes that many companies collect large amounts of data but lack the skills and resources to extract useful insights from it. The document promotes Idiro as a company that can help organizations address common data challenges like too much data to manage, lack of analytical skills, and disparate data sources. Idiro provides tools and expertise to clean, analyze and generate business intelligence from big data to help companies better understand their business and customers.
This document provides a summary of key strategies for successfully scaling artificial intelligence (AI) within an organization. It discusses the importance of having a clear business strategy that AI supports, focusing AI projects on delivering tangible business value. It also emphasizes having the right data strategy to power AI initiatives and taking a portfolio view of AI projects that balances experimentation with alignment to strategic goals. The document recommends challenging assumptions about how work gets done and preparing employees for how AI will change and augment their roles. It argues that organizations must think holistically about scaling AI to realize its full potential for driving business outcomes.
eTailing India Launches Big Data Report - 2015 eTailing India
The document discusses the current state of big data in India and its potential impact on eCommerce growth. It notes that big data involves collecting, processing, and applying insights from large, diverse data sets. While still nascent in India, big data is projected to significantly impact eCommerce by providing deeper customer insights and more personalized experiences. Major players are adopting strategies like Hadoop to analyze customer behavior and improve conversions. Widespread adoption is expected to drive industry competition and innovation.
Companies need to complement their AI initiatives with governance that drives ethics and trust or these efforts will fall short of expectations, our latest research findings suggest.
For the next 40 minutes, I’d like to share with you our experience leveraging AI for businesses.
We’ll first do a tiny little quiz to check your AI knowledge - don’t worry it’s not technical at all.
Then we discuss the common challenges that startups face and give examples on how you can navigate them.
From here, you can do a self-assessment of where you are in the AI maturity journey.
Then we go to through 3 case studies in detail based on their AI maturity. At the end, we also discuss how you can spot opportunities to use AI in your company!
Finally, we close off with a summary and a list of recommendations of no-code AI tools that you can take a look at :)
It’s a loot of content, but the idea is that you will be able to walk away with a renewed understanding of what it takes to build an AI-enabled business but more importantly, how you can be in the driver seat and do it yourself.
We’ll take Q&As at the end and if you have any questions please add them onto Slido :)
Building An AI-Powered Organization To Solve Today’s Business ProblemsBernard Marr
Many organisations have been using technology like artificial intelligence for some time now to transform their businesses, but the current pandemic has created more urgency for companies to automate and innovate.
Artificial intelligence (AI) is getting lots of attention but one key aspect is often overlooked, understated, or underestimated: the quality of “training” information and the structure of that information – the Information Architecture or “IA”. AI only works when it has the data it needs to spot trends, identify patterns and provide functionality – especially when it comes to chatbots and other so called “cognitive” technologies. While many recent high profile attempts at chatbots have failed, they are getting better and one day will be indispensable. Organizations need to do certain things to prepare for a future of bots and AI-driven processes. This session will outline what that looks like and how organizations can solve problems today while preparing themselves for a future where businesses will succeed or fail based on the power of their bots.
This document discusses how artificial intelligence is being used in marketing. It notes that the AI marketing valuation is projected to grow from $12 billion in 2020 to $35 billion in 2024 and $105 billion in 2028. Marketers are using AI for social media analytics to monitor metrics and data. AI allows for highly efficient analysis of consumer engagement and keywords. Marketers can then generate targeted ads. While AI poses privacy and job security concerns, supplementing marketers with AI may help companies succeed. The future of AI in marketing roles and cost benefits is uncertain.
Similar to How To develop An Artificial Intelligence Strategy: 9 Things Every Business Must Include (20)
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