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1、L i t e r a c yThe State ofData&AI2024REPORTThe State of Data&AI Literacy 20241IntroductionSection 1-From data literacy to AI literacy Data and AI skills remain at the heart of improved business performance The evolving data and AI skill gapSection 2-Upskilling&Reskilling in the AI Era AI literacy a

2、s an extension of data literacy Descriptive analytics remain the top priority data skills for leaders The 2024 data and AI competency framework The state of data and AI upskilling and reskilling in 2024Section 3-Five Lessons for Building Your Teams Data&AI Literacy The transformational impact of dat

3、a and AI training Five best practices for succeeding with data and AI upskilling and reskillingSection 4-Beyond the Workplace:Data&AI Literacy as Social Safeguards AI literacy as a safeguard against online misinformation and disinformation AI literacy as a safeguard against potential automation Data

4、 and AI literacy as a safeguard against AI harmsConclusion2371112131518192225283435363839Contents2The State of Data&AI Literacy 2024In last years,we surveyed leaders in the US and the UK about the increasing demand for data literacy skills on their teams.This year,we build on that foundationsurveyin

5、g 550+leaders in the US and the UK and broadening our perspective to include AI literacy.To add to their perspectives,we have collected insights from industry thought leaders and DataCamp for Business customers on many of the themes and trends covered in this report and those for the decades to come

6、.Keep reading and discove?What AI literacy is,and how it intersects withdata literac?The essential data and AI skills leaders are lookingto grow in their teams?Five rules for upskilling and reskilling in the AI er?Why data and AI literacy can act as safeguardsfor humanitys most pressing threatsState

7、 of Data Literacy 2023 ReportGenerative AI has ushered in a paradigm shift,requiring us to reassess the skills needed to succeed in todays AI-driven world.Leaders across the globe are now questioning whether their workforce is equipped to capitalize on this wave of new technology.IntroductionFrom Da

8、ta Literacyto AI LiteracySECTION 1The State of Data&AI Literacy 20244In this first section,we delve into one of the key concepts at the heart of this reportAI literacyand its intersection with data literacy.We explore what these competencies entail,their significance to organizations,and the dynamic

9、s behind the data and AI skill gaps.Since then,the technology landscape has been turned on its head.Generative AI is reshaping industries and business models,and,more importantly,the skills landscape.Fundamentally,it has challenged our conception of data literacy,introducing a new dimension to the c

10、ompetencies required in todays(and tomorrows)workforce.In the past 12 months alone,the.With that comes increased focus on the skills agenda.According to Microsoft,This brings us to the concept of AI literacy,which we define as the ability to effectively,ethically,and responsibly understand,utilize,a

11、nd guide AI systems.usage of tools like ChatGPT at work has doubled82%of leaders say their employees will need new skills to be prepared for the growthof AI.In the 2023 edition of the State of Data Literacy Report,we explored the critical role of data literacy within organizations and society at lar

12、ge.We defined data literacy as the ability to read,write,analyze,communicate,and reason with data,a skill set enabling individuals and organizations to make informed,data-driven decisions.is the ability to read,write,analyze,communicate,and reason with datais the ability to effectively,ethically,and

13、 responsibly understand,utilize,and guide AI systemsData LiteracyAI Literacy5The State of Data&AI Literacy 2024Despite the rapid advancements in AI,the importance of data literacy for organizations remains paramount.In last years report,we saw firsthand how leaders value data literacy skills,with 83

14、%of leaders across the US and UK pointing to data literacy as being important for their teams day-to-day tasks.Today,86%of leaders believe data literacy is important for their teams day-to-day tasks.Moreover,62%of leaders believe AI literacy is now important for their teams day-to-day tasks.The disc

15、repancy in importance between data and AI literacy should come as no surprise,as generative AI tools and systems have yet to be fully embedded in organizations daily workflows.We also surveyed leaders about the growing importance of data and AI skills over the last five years.This same question was

16、posed to leaders in 2023,and the results showed a clear trend:every key data-related skill has seen an increase in importance.Our latest research reveals that 43%of leaders in the US and UK feel data science skills have become significantly more important over the last five years,up from 37%of leade

17、rs in 2023.Similarly,42%of leaders feel that business intelligence skills have become more important,slightly up from 41%in 2023.The perceived importance of basic data literacy skills has also jumped,with 39%of leaders highlighting its growth,compared to 30%in 2023.Additionally,40%of leaders now ide

18、ntify AI literacy as a crucially growing skill,a question that was not included in the 2023 report.It is important to note that the fastest-growing data skill over the past year has been basic data literacy skills.The pace of innovation is rendering data skills a must-have,and is becoming an integra

19、l aspect of almost every role within the organization.As DataCamp for Business customer,Global Director Insights Capabilities at Colgate-Palmolive,puts it:“Data touches all of us,and analytics is an imperative of Colgates transformation.”Taylor Andersonof leaders believe AI literacyis important for

20、their teamsdaily tasks.of leaders believe data literacy is important for their teams daily tasks.Up 3%since last year.The State of Data&AI Literacy 20246Project management skillsData science skillsBusiness intelligence skillsResearch skillsBasic AI literacyBasic computer skillsBasic data literacyPre

21、sentation skillsWriting skillsOther 3%37%37%39%40%40%41%42%43%52%Four of the top seven fastest-growing skills were data and AI skillsQuestion asked:“In the past five years,which skills have grown most important for your team(or department)?Rank by order of importance.”Data skills have grown more in

22、importance for leaders in the past 12 monthsQuestion asked:“In the past five years,which skills have grown most important for your team(or department)?Rank by orderof importance.”Data science skillsBusiness intelligence skillsBasic data literacy 30%41%37%39%42%43%20242023Data touches all ofus,and an

23、alytics is an imperative of Colgates transformation.”Taylor AndersonGlobal Director Insights CapabilitiesColgate-PalmoliveRead Case Study7The State of Data&AI Literacy 2024In the previous section,we highlighted the growing importance of data and AI skills across the board.We wanted to further unders

24、tand the underlying reasons behind this increased importance,focusing on the repercussions leaders face from not having adequate data and AI skills on their teams.We first focused on data skills.Our research uncovered three categories of risk?Poor decision-making:At the forefront,inaccurate(42%)and

25、slow(38%)decision-making emerged as the biggest risks leaders face,highlighting just how important data is for modern decision-making processes and the overall success of a business.?Inability to catch up with the competition:The data also pointed to significant competitive risks,including the threa

26、t of lagging in innovation(30%)and struggling to keep pace with broader competition(23%).Additionally,the risks extend to decreased productivity(36%),which can stall progress and efficiency.?Poor customer experience(25%)and the failure to meet team or departmental targets(24%)further emphasize the c

27、ritical importance of data skills in securing a strong market position and driving organizational success?Poor employee experience:Lastly,leaders were also concerned about employee outcomes,with increased rates of burnout and turnover(17%)and overall poor employee experiences(15%)being top risks fro

28、m not developing adequate data skills.Turning the question on its head shows a similar pattern.When asked about the benefits employees with adequate data skills bring to the table,57%of leaders reported that these individuals make faster and more accurate decisions over those with insufficient data

29、skills,have a stronger capacity for innovation(47%),deliver enhanced customer experiences(41%),possess increased resilience(31%),have higher retention rates(31%),and are more engaged(30%).Data&AI skills remain at the heart of improved business performanceThe data tells a different story when focusin

30、g on AI skills.Leaders perceive the largest risks associated with a lack of AI literacy to be a deficit in innovation(36%),reduced productivity(31%),and an inability to keep pace with competitors(30%).Other concerns include inaccurate decision-making(25%),slow decision-making(22%),unmet team or depa

31、rtmental targets(18%),poor customer experience(18%),burnout and attrition(18%),and subpar employee experience(16%).Reflecting the high value placed on data and AI literacy,theres been a notable rise in leaders willing to pay a premium for employees with these skills.In 2023,66%of leaders were prepar

32、ed to offer higher pay for data literacy,a figure that has climbed to 72%today.Of these,80%are ready to offer at least 10%extra,and 40%would pay 20%or more.While fewer leaders(60%)are inclined to pay a premium for AI skills compared to data literacy,those who do are prepared to offer even higher pre

33、miums.Among these,85%would pay at least an extra 10%,and 46%are willing to increase salaries by a minimum of 20%.The State of Data&AI Literacy 2024Leaders face a variety of risks if they do not build their workforces data skillsQuestion asked:“What risks is your department or team facing if your peo

34、ple do not have adequate data skills?”The value placed on existing employees with adequate data skills shows a similar storyQuestion asked:“What value do data-literate employees provide over those with insufficient data skills?”Inaccurate decision-makingSlow decision-makingDecreased productivityLack

35、 of innovationPoor customer experienceNot meeting targetsInability to catch up to competitionBurnout and employee attritionPoor employee experienceDont knowOther 1%5%15%17%23%24%25%30%36%38%42%Faster decision-makingStronger ability to innovateCreate better customer experiencesMore resilientHigher re

36、tention rateStronger employee engagementDont knowOther 1%6%30%31%31%41%47%57%57%More accurate decision-making 100-5%5-10%10-15%15-20%20-30%30-40%40-50%MoreDont know 2%1%9%11%19%22%18%13%4%Strongly disagreeDisagreeNeither agree nor disagreeAgreeStrongly agreeDont know 2%31%41%19%5%2%9The State of Dat

37、a&AI Literacy 2024Do you agree or disagree with the following statement:When hiring someone new,Im willing to pay a higher salary to a candidate who has good data literacy skills over a candidate who does not.Question asked:“If you answered yes to the previous question,what salary premium are you wi

38、lling to pay to a candidate with high data literacy skills?”Leaders are willing to pay a higher premium for data skills0-5%5-10%10-15%15-20%20-30%30-40%40-50%MoreDont know 1%2%10%11%23%22%17%12%3%Strongly disagreeDisagreeNeither agree nor disagreeAgreeStrongly agreeDont know 4%27%33%23%9%4%10The Sta

39、te of Data&AI Literacy 2024Question asked:“Do you agree or disagree with the following statement:When hiring someone new,Im willing to pay a higher salary to a candidate who has good AI literacy skills over a candidate who does not.”Question asked:“If you answered yes to the previous question,what s

40、alary premium are you willing to pay to a candidate with high AI literacy skills?”Leaders are willing to pay a higher premium for AI skillsThe State of Data&AI Literacy 202411This trend is somewhat counterintuitive;as well see later,organizations have also increased their focus on upskilling and res

41、killing.However,its important to note that upskilling and reskilling on data literacy is a multi-year journey.Moreover,as innovation accelerates,the pressure mounts for organizations to adapt,making the data literacy skill gap even more pronounced.Valerie Logan,CEO of The Data Lodge and inventor of

42、the term“Data Literacy,”put it aptly on a:“We are still in the pioneering phase of data literacyand the pioneers of the data literacy movement are forging the way and making progress,but I would 2023 DataCamp WebinarThe insights from the previous section bring to light the looming threat of the data

43、 and AI skills gap,a challenge that appears to be growing year over year.In 2023,54%of leaders across the US and the UK acknowledged a data literacy skill gap within their organizations.This year,that perception has slightly increased,with 57%of leaders identifying a gap in data skills among their t

44、eams.imagine we are on year 3 of a 10 year wave at the moment”.This year,our research also delved into organizations perceptions of their AI skill gaps,uncovering an even larger disparity.A significant 62%of leaders now recognize an AI literacy skill gap within their organizations.This finding is no

45、t surprising.New technology paradigms,especially those as transformative as generative AI,often introduce entirely new skill requirements.As we stand on the cusp of the generative AI revolution,the AI literacy skill gap will only continue to grow.The evolving data&AI skill gap“We are still in the pi

46、oneering phase of data literacyand the pioneers of the data literacy movement are forging the way and making progress,but I would imagine we are on year three of a 10-year wave.”Valerie Logan,CEO of The Data LodgeWatch the Webinarof leaders believe their organization has anAI literacy skill gap.of l

47、eaders believe their organization has a data literacy skill gap.Up 3%from 2023.57Upskilling&Reskillingin the AI EraSECTION 213The State of Data&AI Literacy 2024In the second section,we zero in on the relationship between AI literacy and data literacy,outlining the specific skills that leaders look f

48、or in their teams.In the previous section,we highlighted how the generative AI revolution has placed AI literacy firmly on the map.This leads us to the following question:where does data literacy end and AI literacy begin?Through discussions with DataCamp for Business customers and observations with

49、in the broader industry,weve come to view AI literacy as a natural extension of data literacy for several reasons.AI has always been partof the data literacy agendaDespite the recent surge in public awareness of AI,its crucial to recognize that generative AI,which has played a major role in the main

50、streaming of AI,represents just one aspect of the broader AI landscape.In reality,machine learning and predictive modeling have long been integral components of the data skills continuum.It could be argued that the most substantial value drivers for organizations today stem from what might be consid

51、ered traditional machine learning and predictive modeling.More importantly,to truly drive value with AI,business teams and technical teams need to adopt a common data language.He mentioned how:“If we can get everyone up to speed when scoping machine learning projects,then business stakeholders and d

52、ata experts can speak the same language and deeply collaborate.By having everyone involved in a project from start to finish,youre not going to run into the trap of having cold feet before a project is deployed.”Eric Siegel,founder of Machine Learning Week,former Columbia professor,and best-selling

53、author,underlined this point during an episode of the DataFramed podcastAI literacy as an extension of data literacyListen to PodcastEric Siegel,Founder of Machine Learning Week,Former Columbia ProfessorThe State of Data&AI Literacy 20249AI will lower the barrierto data literacyAI is increasingly be

54、coming a force multiplier across various domains.From writing to design,AI accelerates the timeto value and lowers the barrier to entry for anyone.Data work is no different.In fact,use cases like programming,reporting,and analysis are emerging as some of the killer apps for generative AI tools such

55、as ChatGPT.Yet,leveraging AI for data tasks demands a nuanced interplay betweenAI literacy and data literacy.,remarking:While all of these tools are extremely helpful,you still have to start with asking the right questions.You have to find a trail of questions and go down that trail.And if you cant

56、find the trailhead,youre not going to get very far on the journey.Now that weve established AI literacy asan extension of the data literacy skill set,what are the top data and AI skills leadersare looking for in their teams?Kyle Daigle,COO of GitHub,highlighted this synergy14Understanding the intric

57、acies of generative AI requires strong data literacyAs we will explore in later sections,understanding basic AI concepts and ensuring the ethical use of AI rank among the top priorities for leaders aiming to enhance their teams AI literacy skills.However,these skills are unattainable without a solid

58、 foundation in data literacy.Identifying biases in algorithms,for instance,necessitates a deep understanding of data collection processes.Similarly,enhancing model performance is closely tied to an intricate knowledge of data governance and quality.,mentioning,“Data skills in the workplace are a hug

59、e asset for people at all ages,all levels,all parts of an organization.”Libby Duane Adams,Co-founder and Chief Advocacy Officer at Alteryx,underscored the importance of data skills for everyone on the DataFramed podcastData skills in the workplace are a huge assetfor people at all ages,all levels,al

60、l parts of an organization.”While all of these tools are extremely helpful,you still have to start with asking the right questions.You have to find a trail of questions and go down that trail.And if you cant find the trailhead,youre not going to get very far on the journey.”Libby Duane AdamsCo-found

61、er and ChiefAdvocacy Officer at AlteryxKyle DaigleCOO of GitHubListen to PodcastListen to Podcast15The State of Data&AI Literacy 2024As organizations course-correct,it should be no surprise that descriptive analytics are the most important skills leaders are looking to build in their teams.More inte

62、restingly,almost every single dataskill grew in importance in comparisonto last year.We asked leaders to rank the data skills they deem most important for their teams.The results underscore a clear emphasis on data-driven decision-making,and being able to make sense of complex datasets.Leading the p

63、ack,84%of leaders pointed to data-driven decision-making as the most important skill for their teams(up by 6%since last year).Following closely,83%of leaders found that the ability to interpret data visualizations and dashboards(up by 9%)was most important to build.80%of leaders found data analysis

64、and manipulation skills to be most important(up by 8%),and 76%of leaders stressed the importance of creating data visualizations and dashboards(up by 11%)as the most important data skill for their teams.Unpacking the data&AI skills leaders are looking to grow in their teamsFinally,74%of leaders iden

65、tified data storytelling as the most important skillfor their teams(up by 8%).Not to be overlooked however was knowledge of tools.74%of leaders pointed to knowledge of Business Intelligence tools(up by 11%)as the most important data skill their teams needed to know.SQL skills are also deemed a prior

66、ity,with 65%of leaders(up by 12%)mentioning database skills as the most important for their teams.A similar story emerges for programming,machine learning,and data engineering skills.59%of leaders pointed to machine learning and data engineering skills being the most important for their teams(up by

67、12%and 7%,respectively),and 54%discussed programming skillsin R or Python as the most importantfor their teams(up by 12%).So far,weve uncovered the dynamics behind the data and AI literacy skill gap and highlighted the growing importance of these skills in the modern workplace.Weve also contextualiz

68、ed AI literacy in relation to data literacy.Now,we turn our focus to the specific skills leaders are looking to grow within their teams.Descriptive analytics remains thetop priority data skill for leadersIn,we outlined how one of the biggest driversof the data literacy skill gap originally came from

69、 organizations prioritizing predictive analytics use cases over growing the descriptive analyticschops of their workforce.last years State of Data Literacy Report16The State of Data&AI Literacy 2024Question asked:How important,if at all,are the following data skills for the day-to-day tasks of emplo

70、yees in your organization?”Not ImportantSomewhat ImportantImportantVery ImportantData skills have grown in importance for leaders,with descriptive analytics being a top skill leaders are looking to grow+6%Change in importance since last year+9%+8%+11%+11%+8%+7%+12%+12%+12%Data-driven decision-making

71、Interpreting data visualizations&dashboardsData analysis and manipulationCreating data visualizations&dashboardsBusiness intelligence toolsData storytellingWorking with databasesData engineeringMachine LearningProgramming34%33%34%34%41%42%41%50%46%54%21%26%25%31%33%32%35%30%37%30%12%19%19%15%14%16%1

72、5%13%12%10%33%22%22%20%12%10%9%7%5%6%17The State of Data&AI Literacy 2024Understanding AI concepts and responsible use of AI are top AI skills leaders need from their teamsExpanding this years survey to cover AI,we asked leaders to identify the most important AI skills for their teams.Leading the ch

73、arge,70%of leaders identified a basic understanding of AI concepts as most important for their team,emphasizing the necessity for teams to grasp the core principles underlying AI technologies.AI ethics and responsible AI best practices closely followed,with 69%of leaders highlighting them as the imp

74、ortant AI skills for their teams.The application of AI in business contexts was also a key focus,with 65%of leaders recognizing its importance.Surprisingly,despite the buzz around generative AI tools like ChatGPT,leaders ranked prompt engineering and steering the outputs of AI systems as the fourth

75、most important skill for their team,with 60%of leaders believing it is the most important.Developing AI systems from scratch was deemed important by 52%of leaders,pointing to the need for technical proficiency in AI development within teams.This skill highlights the importance of having in-house cap

76、abilities to create and tailor AI solutions.The ranking of these skills highlights a pressing need for basic AI understanding and ethical AI use in organizations.Leaders are putting a lot of weight on getting the basics of AI right and making sure its used ethically,showing how important it is to ca

77、refully consider AIs potential effects.This approach is crucial not only for making the most of what AI has to offer but also for avoiding the negative impacts and damage to reputation that can happen if AI is used carelessly.While theres recognition for the skills needed to use advanced AI tools li

78、ke ChatGPT,its interesting to see these take a backseat to more fundamental and ethical concerns about AI.Question asked:How important,if at all,are the following AI skillsfor the day-to-day tasks of employees in your organization?”Basic understanding of AI concepts and responsible use of AI are the

79、 most important skills leaders are looking from their teamBasic understandingof AI conceptsAI ethics&responsible AI AI applications in business31%32%35%41%43%21%27%31%27%27%12%18%20%16%18%36%23%14%16%12%the outputs of AI systems Prompt engineering and steeringDeveloping AI systems from scratchNot Im

80、portantSomewhat ImportantImportantVery ImportantThe State of Data&AI Literacy 202411The 2024 Data&AICompetency FrameworkAccess The Data Competency FrameworkIn last years State of Data Literacy 2023 Report,we introduced our data competency framework.This framework looked at the entire spectrum of dat

81、a skills organizations may want to grow within their workforce and has been used by DataCamp for Business customers,data leaders,and learning leaders across the world.Data&AI Competency FrameworkCommunicating with Data&AIWorking with Data&AI?Data storytelling:The art of effectively communicating ins

82、ights and findings from data analysis?Understanding data science concepts:Being knowledgeable and conversational about the methods,theories,and tools used in the field of data science?Understanding data engineering concepts:Being familiar with the processes and technologies involved in designing,con

83、structing,and maintaining data pipelines and infrastructure?Understanding machine learning concepts:Being knowledgeable about the possibilities and limitations of machine learning and the techniques used to train and operate predictive models?Understanding AI concepts:Being familiar with key AI tech

84、nologies,such as ChatGPT,Large Language Models,and Generative AI?AI applications for business:Understand how to utilize AI and Large Language Models to extract business value from AI.?Data wrangling and manipulation:Transforming and organizing data for analysis?Predictive modeling and machine learni

85、ng:Training and using predictive models to make predictions about future events?Data engineering:Designing and building the infrastructure and processes for collecting,storing,and analyzing data?Programming:Mastery of programming languages to perform data-related tasks.?Importing and cleaning data:R

86、eading data from various sources and ensuring they are free of data quality issues?Data visualization and dashboard design:Creating graphical representations of data and designing interactive dashboards for data exploration and analysis?Developing AI systems:Create production-ready AI applications,b

87、uild and fine-tune LLMs for specific use cases?Responsible AI:Understand the ethical implications of using AI and leverage AI responsibly?Working with and steering AI systems:Leverage ChatGPT and other LLMs to automate routine tasks and drive workflow efficiencies.Curriculum Cheat Sheet For Every Sk

88、ill Level02Reasoning with Data&AI?Business analysis:Using data and analysis to understand and improve business processes and operations?Statistical analysis:Using statistical methods to analyze and make inferences from data?Reporting with data:Presenting data-based findings and insights clearly and

89、concisely.Reading Data?Interpreting data insights and visualizations:Understanding and making sense of data-based findings and their representations?Data-driven decision-making:Using data and analysis to inform business decisions.Below you will find an updated competency framework including keyAI li

90、teracy skills covered throughout this report.We highly encourage you to use this when building your data and AI upskillingand reskilling programs.Data&AI Competency FrameworkThis framework oversees the entire spectrum of data and AI skills you may look to grow within your workforce.On the next page,

91、we will introduce key personas and roles and will match skills and learning paths for each of them.At DataCamp,we identify four key groups of competencies:and with data and AI.communicating,reading,reasoning,workingCurriculum Cheat Sheet For Every Skill Level01Responsible AIWorking with and steering

92、 AI systemsUnderstandingAI conceptsAI applications for businessAI systemsmodeling&N/ABeginnerIntermediateAdvanced1819The State of Data&AI Literacy 2024So far,weve explored the data and AI skills leaders are looking to grow in their teams.In this section,we wanted to understand how leaders are approa

93、ching filling the data and AI skills gap and what their biggest challenges are when future-proofing their teams skillsMore interestingly,theres been a 4%increase in organizations with mature data literacy programs that are available to everyone,with 35%of leaders mentioning data training is availabl

94、e to all,as opposed to 31%in 2023.Despite the positive signals,there is still much room for growth.The expansion of data upskilling and reskilling programs hasnt kept pace with the increasing demand for data skills.While leaders approach to data upskilling shows signs of progress,the story changes w

95、hen examining AI upskilling and reskilling.A concerning 26%of leaders report that they do not offer any form of AI training.An additional 26%of leaders point to AI training being reserved for technical roles only,whereas only 18%extend such training to non-technical staff.Finally,25%of leaders belon

96、g to organizations that have established comprehensive,organization-wide AI literacy programs.These figures show that AI skills transformation is still in its infancy,as the level of urgency and action taken to address the AI skills gap appear to lag a few years behind those forthe data skills gap.T

97、he stateof data&AI upskilling&reskilling in 2024Despite progress,data and AItraining remains in its infancyWhen prompted about the state of data training within their organization,leaders report signs of gradual improvement.Only 12%say they offer no data training,down from 18%last year.On the flip s

98、ide,more organizations are expanding data training to non-technical roles,increasing from 14%to 20%over the past year.19The State of Data&AI Literacy 2024Question asked:What would best describethe state of data training at your organization?”Question asked:What would best describethe state of AI tra

99、ining at your organization?”Data and AI training remains nascent in organizationsWe do not o er any form of datatraining at my organizationOnly employees in some technicalroles receive data trainingOnly some employees outside oftechnical receive data trainingliteracy upskilling program for all emplo

100、yeesDont knowWe have a mature,organization-wide data We have a mature,organization-wide AI Dont knowOnly some employees outside oftechnical receive AI trainingWe do not training at my organizationoffer any form of AIroles receive AI trainingOnly employees in some technicalliteracy upskilling program

101、 for all employees12%20%29%20%20%18%35%25%4%6%20The State of Data&AI Literacy 2024Blended learning:The preferred approach to bridging the data and AI skills gapWhen leaders were asked about their preferred methods for training teams in data and AI skills,30%preferred blended learning as the top choi

102、ce.This method combines online learning with conventional instructor-led sessions to effectively close the data and AI skills gap within their teams.Additionally,18%rely exclusively on third-party online training,and 17%develop their own online learning materials.Furthermore,10%of leaders emphasized

103、 that instructor-led sessions are the key method for upskilling their teams in data and AI skills,while 18%reported that they do not provide any form of data and AI training.21Question asked:How do you upskill your workforce on data and AI skills?”Blended learning and online learning are the most po

104、pularways of addressing the data and AI skills gap18%We do not provide data&AI training18%Third-party online-based training providers17%Internally created online-based training10%Instructor-led sessions8%Dont knowBlended learning30%The State of Data&AI Literacy 2024The challenges leaders are facingi

105、n filling the skills gapAs we reflect on how leaders are training their teams in data and AI and considering the urgency of filling the skills gap,its important to also highlight the main challenges leaders face when upskilling and reskilling their teams on data and AI.Lack of budget and inadequate

106、training resources top the list of challengesWhen leaders were asked to identify the top challenges in training their teams,35%cited a lack of budget as the primary obstacle.This represents a slight improvement from the 40%reported last year but remains the most significant barrier to the transforma

107、tion of data and AI skills.Following closely,inadequate training resources emerged as the second major hurdle,highlighted by 33%of leaders who pointed to the quality of learning materials as a key issue.The third most common challenge,cited by 31%of leaders,is the difficulty in knowing where to star

108、t with data and AI training,which impedes the ability to drive meaningful impact.Other notable challenges are more related to organizational culture,with 28%of leaders reporting employee resistance and 26%noting a lack of executive support and clear ownership of training programs as significant obst

109、acles to successful upskilling.Online learning resources do not provide the needed level of personalization and interactivityIn earlier sections,we learned that at least 65%of leaders utilize online resources for data and AI upskilling and reskilling.However,33%of these leaders indicate that a lack

110、of adequate training materials is the primary obstacle to achieving success in data and AI skills.What is driving this dissatisfaction?22Question asked:What challenges have you faced or currently facing whenimproving your workforces data and AI skills?Please select all that apply.”Lack of budget and

111、 inadequate trainingresources top the list of challengesLack of budgetInadequate training resourcesInability to understand how to get startedEmployee resistanceLack of executive supportLack of ownership of the training programNone of the above35%33%31%28%26%26%16%The State of Data&AI Literacy 2024A

112、notable 29%of leaders find that video-based courses make it difficult to apply learned skills in the real world,pointing to lack of interactivity as the biggest challenge with online learning.Similarly,29%of leaders point to employee confusion about where to get started as the biggest challenge they

113、 face with online learning providers.This should come as no surprise,as the majority of todays online learning platforms opt for a volume over curation approach(for example,Coursera has over 250 near-identical courses providing an introduction to Python,and Udemy has over 3000).24%of leaders point t

114、o lack of personalization and inability to trackROI on data training as their biggest challenges.More interestingly,20%of leaders point to lack of certifications for learners as the biggest obstacle to driving value with third-party online training providers.22Question asked:If you use a third-party

115、 online training provider,what challenges have you faced?Please select all that apply.”Online learning resources do not provide the needed level of personalization and interactivityVideo-based courses make it dicultto apply learned skills in the real worldInability for employees to understandwhere t

116、o start learningThe skills people learn arenot relevant to their rolesInability to report on the returnon investment data trainingWe do not o er any form of data&AItraining at my organizationLack of certi cations for learners29%29%24%24%21%20%Experience personalized interactive learning with DataCam

117、pWhether data literacy for beginners,or machine learning for developers,your teams will put their skills into action with hands-on interactive exercises,right in the browser.23Five Lessons for Building Your Teams Data&AI LiteracySECTION 3The State of Data&AI Literacy 2024In this third section,we exp

118、lore how leaders are adapting their upskilling and reskilling programs for the AI era and the best practices you can adopt in your organization.Whats interesting here is that these are aggregate numbers;lets see what happens when we cross-section the results based on data and AI upskilling program m

119、aturity.When looking at results from leaders who have either a mature organization-wide data literacy program or a mature organization-wide AI literacy program,we can see significant increases in the benefits received from data and AI training.Leaders with either mature data and AI literacy programs

120、 report seeing even more benefits in the form of faster decision-making(90%),improved decision-making(88%),better innovation(87%),improved customer experience(81%),decreased costs(84%),increased revenue(81%),and better employee retention(81%).More interestingly,the number of leaders pointing to a co

121、mplete transformation of these competencies as a result of widespread data and AI training has also increased.The following charts clearly show that while the benefits of data and AI upskilling are visible regardless of the scale of the program,organizations with organization-wide data and AI litera

122、cy programs are likely to accrue the most benefit from training.The transformational impactof data and AI trainingBefore jumping into the best practices for building your teams data and AI skills,lets examine the value leaders with existing data and AI training programs have brought to their organiz

123、ations.Across the board,leaders highlight numerous positive outcomes resulting from data and AI training initiatives.These benefits cover a wide range of categories,including faster decision-making(76%),improved decision-making(75%),better innovation(75%),improved customer experience(65%),decreased

124、costs(66%),increased revenue(64%),and better employee retention(62%).242526The State of Data&AI Literacy 2024Question asked:How has your organization benefited from data and AI training?”Did Not ImproveSlightly ImprovedSignificantly ImprovedDont KnowCompletely TransformedLeaders with data and AI tra

125、ining programs of any size have seen benefitsImproved decision-makingFaster decision-makingBe er innovationImproved CXBe er retentionIncreased revenueDecreased costs23%26%26%29%20%20%20%17%19%18%21%26%23%26%27%28%28%27%26%30%27%22%17%16%17%23%23%22%11%10%12%6%5%4%5%27The State of Data&AI Literacy 20

126、24Question asked:How has your organization benefited from data and AI training?(Only mature data and AI training programs)”Leaders with mature data and AI training programs have seen the most benefits from data and AI trainingImproved decision-makingFaster decision-makingBe er innovationImproved CXB

127、e er retentionIncreased revenueDecreased costs10%12%11%13%8%7%7%30%27%30%33%41%36%40%35%42%39%37%31%39%35%20%12%13%11%15%16%14%5%7%7%6%5%2%4%Did Not ImproveSlightly ImprovedSignificantly ImprovedDont KnowCompletely TransformedThe State of Data&AI Literacy 20242525The launch of ChatGPT made AI access

128、ible to the world.However,AI and machine learning have always been a part of the data language.We shouldnt be distinguishing between AI and data literacy;they are both complimentary skill sets that will help us move forward in a more data-driven and analytical world.”Jordan MorrowBest-selling author

129、,Godfather of data literacy,SVP of Data&AI Transformation at AgileOne,and DataCamp InstructorWatch the WebinarFive best practices for succeeding with data and AI upskilling and reskillingExpand your existing data upskilling program to focus on AI literacyIn the earlier sections of this report,we hig

130、hlighted the strong connection between AI literacy and data literacy.Additionally,we observed that AI training initiatives lag behind data training initiatives,both in maturity and in scope.This gap needs to be addressed,and an easy,practical way of addressing it is by expanding existing data litera

131、cy programs to incorporate AI skills.This not only accelerates the bridging of skills gaps but also enables your workforce to contextualize data and AI literacy as interconnected skill sets.,stating:“The launch of ChatGPT made AI accessible to the world.However,AI and machine learning have always be

132、en a part of the data language.We shouldnt be distinguishing between AI and data literacy;they are both complimentary skill sets that will help us move forward in a more data-driven and analytical world.”Jordan Morrow,best-selling author,Senior Vice President of Data and AI Transformation at AgileOn

133、e,Godfather of the term“data literacy”and DataCamp Instructor,emphasizes the importance of treating AI literacy like an extension of data literacy2528The State of Data&AI Literacy 2024A compelling example of this approach is demonstrated by.Colgate partnered with DataCamp for Business and upskilled

134、14,860+employees on data literacy as part of its broader Data Literacyand Analytics Academy.The program boasted large success,with 80%of learners applying newly learned skills in real-world settings.However,as it became clear that Generative AI skills will be foundational for Colgate moving forward,

135、they quickly evolved their upskilling program to incorporate AI,and worked with DataCamp on providing 18,000 Colgate learners with access to DataCamps ChatGPT and Generative AI content.Colgate-Palmolives upskilling program25“I just finished DataCamps AI training.One of the great things about it is t

136、hat it gives us a common understanding and a common language to use in the organization.Not to mention the modules are short,they are easy to integrate into the flow of work.”Amanda Klemm,World Wide Director,Manual Toothbrushes at ColgateRead Case Study29From data pleting data literacycourses on Dat

137、aCampcompleting generative AIcourses on DataCamp.to AI literacyHow Colgate-Palmolive Adapted its Data Upskilling Program14,860+learners18,000+learnersThe State of Data&AI Literacy 2024If you have an upskilling program in place,its time to expand it to a wider populationSo far,weve showcased the posi

138、tive correlation between organization-wide upskilling initiatives and improved transformative outcomes coming from upskilling.Therefore,its only logical that our second best practice involves broadening the scope of these programs to reach a larger audience.This is especially relevant when it comes

139、to AI literacy,where the adoption of tools like and when looking at the AI skills leaders are looking for from their teams.As we saw earlier,leaders are primarily focused on a basic understanding of AI concepts and responsible AI best practices as the most important AI skills their teams need to kno

140、w today.ChatGPT in the workplace has more than doubled in the past year aloneBeena Ammanath,Global Head of the Deloitte AI Institute,elaborated on the intersection of AI literacy for all and Responsible AI during her discussion on the DataFramed podcastShe highlighted in an the importance of scope a

141、nd personalization of AI upskilling initiatives,mentioning:“In the C-suite,each business leader contends with issues specific to their role.AI literacy means,in part,understanding how AI functions in the context of their work.What is relevant to the chief marketing officer may not be the same for hu

142、man resources,accounting,or finance.”Center interactivity and personalization at the heart of your learning programSo far,our report has highlighted a lack of personalization and interactivity as significant challenges in online learning.This is especially the case for technical skill development li

143、ke programming,knowledge of business intelligence tools,and working with databases,where skills acquired require an active learning method rather than a passive one.external publicationA prime example of how personalization and interactivity can accelerate technical skills development comes from Rol

144、ls Royce.and leveraged the track editor feature to build tailored learning tracks comprising relevant,interactive Python courses for its engineers.As a result,engineers could swiftly integrate newfound knowledge,accelerating the design process and reducing its duration bya factor of one hundred.Roll

145、s Royce worked with DataCamp for Business2630In the C-suite,each business leader contends with issues specific to their role.AI literacy means,in part,understanding how AI functions in the context of their work.What is relevantto the chief marketing officer may not be the same for human resources,ac

146、counting,or finance.”Beena Ammanath Global Head of the Deloitte AI InstituteAkin KeskinChief of Design Systems,Rolls-RoyceListen to PodcastRead Case StudyAt Rolls-Royce,were dealing with complex data sets related to airlines and engines.Through DataCamp,our engineers gained valuable experience and l

147、earned how to automate multiple data handling processes that previously had to be completed manually.”The State of Data&AI Literacy 202424Weve begun to build a ritual using DataCamp to set fun challenges followed by presentations for our internal data community.So far,weve had around 45 completed ch

148、allenges.Over time,well buildan expectation around these challenges,which were runningon an approximately monthly schedule.Using DataCamps gamification,were able togenerate some real energyfor data learning.”Lorraine PocklingtonData Community Manager at SpecsaversRead Case Study31Another good exampl

149、e comes from,which leveraged DataCamps gamification features(learner XP,leaderboards)to drive even more engagement with learners as part of competitions.Specsavers suffered from skill gaps in Power BI and Databricks,and increased dependency on spreadsheets.They worked with DataCamp for Business to a

150、ddress these skill gaps.While they leveraged features like tailored learning paths and advanced reporting,a key highlight of their program was their use of gamification and leaderboards to drive engagement with learners.As a result,Specsavers experienced 3-4 hours saved per week per employee upskill

151、ed across 115+individuals.Given this,if your current online learning platform lacks interactivity and personalization,consider transitioning to a platform like DataCamp.Alternatively,if an immediate switch is not feasible,here are some tactics to quickly embed interactivity and personalization into

152、your program.SpecsaversQuick tactics forbetter interactivity?Host instructor-led sessions with internal experts,tasking learners with solving real-world use case?Integrate gradable capstone exercises at the end of learning track?Incorporate gamification elements,such as leaderboards,badges,or reward

153、s to make learning engaging?Establish sub-communities within your learning community(e.g.Marketing Analytics Community)?Organize lunch-and-learns with functional or departmental leader?Incorporate relevant industry or department-focused resources into your upskilling program,such as the or our DataF

154、ramed podcastweekly webinarsQuick tactics forbetter personalizationQuick tactics for adding interactivity andpersonalization in your learning programThe State of Data&AI Literacy 202425“There are three things that generative AI can do.It can summarize text very,very efficiently.It can create content

155、 in a very efficient manner.The third way that Ive seen it implemented is around code generation or code interpretation.”Nick Magnuson,Head of AI at QlikListen to Podcast32Treat AI literacy like a force multiplierfor your data upskilling programCounterintuitively,tasks central to data,such as analys

156、is and programming,have surprisingly been one of the killer apps of tools like ChatGPT.Weve seen this firsthand with the launch of DataLab and its transformative potential of reducing the barrier to entry to meaningful data work.Weve also corroborated this notion in our survey.When asked,“Do you agr

157、ee or disagree with the following statement:AI will make it easier for my team to work with and draw insights from data”a notable 73%of leaders agreed.,highlighting the implications of generative AI on data-related tasks.Nick Magnuson,Head of AI at Qlik,further elaborated on this point on the DataFr

158、amed podcastHe mentioned:“There are three things that generative AI can do.It can summarize text very,very efficiently.It can create content in a very efficient manner.The third way that Ive seen it implemented is around code generation or code interpretation.”As such,in line with our first best pra

159、ctice,we recommend you treat building your organizations AI literacy as a force multiplier of your existing data literacy initiatives,as AI skills will enable everyoneto accelerate the adoption of newly acquired data skills.Be proactive about change management and positive reinforcementThe introduct

160、ion of data and AI technologies into the workplace offers significant potential for better decision-making,innovation,and productivity.However,it would be foolish to ignore the feelings of fear and anxiety they bring to the wider workforce.According to,74%of employees report feeling overwhelmed when

161、 working with data.Conversely,reports that 4 in 10 workers express concerns about AI automating their roles.Stress and anxiety are common responses to the evolving skills landscape.To address these challenges,being proactive about addressing these concerns is essential.Leaders should cultivate a pos

162、itive vision for the future and implement effective change management strategies.Qlik and AccentureCNBC and SurveyMonkeyof leaders believe that generative AI will reduce the barrier to entry for working with data.73The State of Data&AI Literacy 2024Andrew McAfee,Principal Research Scientist at the M

163、IT Sloan School of Management,came on the DataFramed podcast and emphasized the importance of evolving organizational norms and values to create a happy and effective organization.He mentioned that rather than solely focusing on checklist-style training initiatives,leaders should focus on revamping

164、cultural norms and values and proactively celebrating early adopters.He mentions:“A relentless emphasis on winning will tank you over time.The way you make an organization better is not by sending people off to cutting-edge training on data science or AI ethics or whatever else.Its by getting the ri

165、ght norms in place;then youve got community momentum that takes the organization in the direction you want it to take.”In driving positive change management for the purposes of data and AI transformation,consider adopting five tactics outlined below?Clarify and consistently repeat the“Whats in it fo

166、r me”of data and AI upskilling?Be proactive about addressing concerns related to automation and focus on dispelling the notion that data will be used to punish?Celebrate early adopters and ensure that leaders are celebrating cultural change agents?Leverage early adopters and build decentralized netw

167、orks of champions that advocate for yo?Have leaders lead by example by opening meetings with data or sharing best practices for the use of AI at work2633A relentless emphasis on winning will tank you over time.The way you make an organization better is not by sending people off to cutting-edge train

168、ing on data science or AI ethics or whatever else.Its by getting the right norms in place;then youve got community momentum that takes the organization in the direction you want it to take.”Andrew McAfeePrincipal Research Scientist at the MIT Sloan School of ManagementListen to PodcastBeyond the Wor

169、kplace:Data&AI Literacy as Social SafeguardsSECTION 435The State of Data&AI Literacy 2024In this section,we explore the implications data and AI literacy hold for societal challenges like misinformation,automation,and bias from AI systems.In previous sections,weve explored how data and AI literacy c

170、an drive positive outcomes for organizations and their workforce.However,beyond the workplace,these competencies are emerging as essential life skills that serve as societal safeguards against humanitys most pressing threats.These threats include online misinformation and disinformation,the potentia

171、l impact of automation,and the risks associated with the widespread deployment of AI.Lets learn how data and AI literacy can help mitigate these threats.AI literacy as a safeguard against online misinformation and disinformationAccording to the,misinformation and disinformation represent the most si

172、gnificant risk facing humanity in the immediate future.World Economic Forum Global Risks Report 2024This is especially concerning given that generative AI has the potential to reduce the cost of spreading misinformationand disinformation to zero,particularlyduring critical election cycles.We asked l

173、eaders to comment on the potential impact AI literacy has on protectingus from online misinformation and disinformation.73%of leaders agree that AI literacy is fundamental for combatting online misinformation.However,addressing these challenges requires more than just literacy;it necessitates a robu

174、st AI governance framework.As discussed by,such a frameworkis vital for managing the multifaceted implications of AI in society.Ian Bremmer,Political Scientist and Founder and President of Eurasia Group,and Jimena Viveros,Chief of Staff and Head Legal Advisor to Justice Loretta Ortiz at the Mexican

175、Supreme Court,on the DataFramed podcastThe State of Data&AI Literacy 202436Our survey of leaders reflects a similar sentiment,with six out of 10 leaders agreeing AI will inevitably lead to some level of job automation within their organizations.However,amidst these concerns,leaders also identify AI

176、literacy skills as a crucial defense against automation.57%of leaders believe that employees with AI literacy skills are less susceptible to being impacted by automation.Moreover,theres a recognition among leaders that organizations and countries bear a responsibility to ensure that individuals are

177、not left behind in the face of technological advancements.In fact,75%of leaders agreed that countries and organizations bear a responsibilityto equip their people with the necessary data and AI skills to remain competitivein todays job market.At DataCamp,we share this responsibility to prepare indiv

178、iduals for a digital future.Since last year,with our Donates and Classrooms programs,ensuring they remain competitive in todays AI-driven job market?weve upskilled over 1 million people for freeThey mentioned:“The reason we need a global governance framework is because historically,when new technolo

179、gies are driven by massive market forces,we are very good at privatizing the gains that come from those and we frequently socialize the losses.Thats even true ina great capitalist country like the United States.That means that you get all sortsof negative externalities that no onewants to pay attent

180、ion to.”Combining Ian and Jimenas insights with the ones reported by leaders,we realize that AI literacy not only helps mitigate immediate risks like misinformation but also empowers individuals to engage in meaningful dialogues with government institutionsand help shape the future of AI regulation.

181、AI literacy as a safeguardagainst potential automationThroughout this report,weve witnessed firsthand the anxiety surrounding the potential impact of generative AI on job security,with.four in 10 workers expressing anxiety about AI potentially displacingtheir rolesThe reason we need a global governa

182、nce framework is because historically,when new technologies are driven by massive market forces,we are very good at privatizing the gains that come from those and we frequently socialize the losses.Thats even true in a great capitalist country like the United States.That means that you get all sorts

183、 of negative externalities that no one wants to pay attention to.”Ian BremmerPolitical Scientist,Founder andPresident of Eurasia GroupListen to PodcastThe State of Data&AI Literacy 2024While theres no guaranteed shield against automation risks,.He notes that while some displacement is inevitable,aug

184、mentation of current jobs with AI will most likely be the prevailing scenario,and knowinghow to leverage AI will be fundamental to succeeding in these newly augmented jobs.Bernard Marr,AI Advisor,Best-Selling Author,and Futurist,underscores the importance of AI skills as a means to protect ourselves

185、 from potential displacement25“There will be some job displacement for sure,but the vast majority of jobs will be augmented,and where AI will almost give us a superpower that works alongside us and will make us better and more efficient and hopefully more human in the long run.And what people should

186、 be worried about is not AI,but people using AI better than they are in order to become better at their job.”Bernard Marr,AI Advisor,Best-Selling Author,and FuturistListen to Podcast37agreed that countries and organizations are responsible for ensuring their people have the necessary data and AI ski

187、lls to remain competitive.of leaders believe that individuals withAI literacy skills are less likely to be impacted by automation.7557of leaders believe that AI will leadto some form of automation withintheir organizations.62The State of Data&AI Literacy 202424Were building AI systems involving huma

188、ns.Language by itself is imbued with so much of our biases.The ways in which we describe certain things like“Policeman”or“Mankind.”What are we inferring with the use of that terminology?There are many things that are embedded in the ways that we speak that we might think is normal,but was actually c

189、onstructed.Being aware of that allows us to actually build better technical systems because technical systems are never divorced from us.”Dr.Joy BuolamwiniArtist-in-Chief and President of The Algorithmic Justice LeagueListen to Podcast38Data and AI literacy as asafeguard against AI harmsAs highlight

190、ed earlier,the ethical and responsible use of AI stand out as one of the most sought-after skills by leaders for their teams.Going deeper into this,a significant 75%of leaders agreed with the statement,The responsible and ethical use of AI should be taught to every employee in my organization.This s

191、entiment is well-founded,considering the potential for both generative and discriminative AI to inflict significant harm,particularly in terms of bias.She emphasized the prevalence of bias in current machine learning models,mentioning:“Were building AI systems involving humans.Language by itself is

192、imbued with so much of our biases.Dr.Joy Buolamwini,Artist-in-Chief and President of The Algorithmic Justice League,shed light on the pervasive nature of bias in machine learning systems during her discussion on the DataFramed podcastThe ways in which we describe certain things like“Policeman”or“Man

193、kind.”What are we inferring with the use of that terminology?There are many things that are embedded in the ways that we speak that we might think is normal,but was actually constructed.Being aware of that allows us to actually build better technical systems because technical systems are never divor

194、ced from us.”As a result,data and AI literacy emerge not only as essential skills for driving improved business outcomes but also as foundational safeguards against the inadvertent deployment of harmful AI systems.The work on this report began in early February 2024.At that time,the world was and co

195、ntinues to grapple with the profound implications of transitioning to an AI-driven landscape.Throughout this report,weve witnessed firsthand the growing importance of the upskilling and reskilling agenda.However,its clear that this urgency has not matched the pace of the rapidly evolving skill requi

196、rements demanded by leaders in this new era.At DataCamp,weve had the privilege of collaborating with numerous organizations in bridging their data and AI literacy skill gaps.With these partnerships,well continue to champion the inspiring stories of leaders at the forefront of driving data and AI lit

197、eracy initiatives within their teams and organizations.If youre looking to be part of this journey,speak to our team today.ConclusionThis research has been conducted using an online interview administered to members of the YouGov Plc UK and USA panel of individuals who have agreed to take part in su

198、rveys.In this research,the survey features the opinions of a sample of 564 business leaders in the UK and the USA.The data was collected between 22.01.2410.02.24,and all the qualitative interviews referenced with thought leaders in the data and education space were featured from the DataFramed podca

199、st and DataCamps webinars and RADAR conference series.Methodology39The State of Data&AI Literacy 2024Subscribe to theDataFramed podcastSign up to anupcoming webinarWatch DataCampRADAR recordingsListen HereWatch HereWatch HerePanel of expertsTaylor AndersonGlobal Director Insights Capabilities at Col

200、gateJordan MorrowBest-selling author,Godfather of data literacy,and DataCamp InstructorAndrew McAfeePrincipal Research Scientist at the MIT Sloan School of ManagementBeena AmmanathGlobal Head atDeloitte AI InstituteIan BremmerPolitical Scientist&Founder&President of Eurasia GroupAkin KeskinChief of

201、Design Systems at Rolls-RoyceLorraine PocklingtonData Community Manager at SpecsaversBernard MarrAI Advisor,Best-Selling Author,and FuturistNick MagnusonHead of AI at QlikDr.Joy BuolamwiniArtist-in-Chief and President of The Algorithmic Justice LeagueValerie LoganCEO at The Data LodgeLibby Duane Ada

202、msCo-founder and Chief Advocacy Officer at AlteryxKyle DaigleCOO at GitHub40Eric SiegelFounder of Machine Learning Week,Former Columbia Professor,Best-selling AuthorJimena ViverosChief of Staff and Head Legal Advisor to Justice Loretta Ortiz at the Mexican Supreme CourtThe State of Data&AI Literacy

203、2024Youre in great companyMore than 4,000 organizations use DataCamp to transformhow their teams use data and AI.Read the case studyRead the case studyRead the case studyRead the case studyRead the case studyRead the case studyThe State of Data&AI Literacy 202441Empower your business with world-clas

204、s data and AI skillsDataCamp is the go-to data and AI transformation platform.Equip your workforce with the skills and toolsto work with data and AI at scale.Make data-driven decisionsat scaleEmpower your workforce to make fasterand better decisions with data.Drive technology adoptionDrive technolog

205、y ROI by equipping your workforce withthe necessary skills to work with modern data and AI tools.Accelerate growth and innovationDrive and sustain innovation and enable yourworkforce with a common data and AI language.Retain and attract talent effectivelyMake skills the key to retaining and attracti

206、ng toptalent with tools to easily drive learner engagement.The DataCamp EdgeA comprehensive data and AI curriculumBuild your team data skills with a top-tier curriculum focused only on data and AI skills,spanning introductory data literacy skills to advanced machine learning.A hands-on interactive l

207、earning experiencethat worksWhether conceptual or coding courses,your team will put their skills into action with short videos and hands-on interactive exercises.Learnerreporting and analyticsVisualize skillgrowth across your organization and seamlessly integrate learning data into your reporting to

208、ols.World-class support andguidanceGuarantee learningsuccess with supportfrom customer success managers on adoption strategies,roll out best practices,SSO,and LMS integrations to tailorlearning paths that fityour organization perfectly.Learn why 14M+learners and 4,000+organizations prefer DataCamp for data and AI upskilling.With DataCamp,build everyones data and AI skills,from busy executives to front-line workers.Thank you for readingAre you an organization interested in scalingyour data and AI literacy skills?Speak to Our Sales Team Today