Edit (as of 2021-03)

As also pointed out in Eric’s answer, mutate_[at|if|all] has been superseded by a combination of mutate() and across(). For reference, I will add the respective pendants to the examples in the original answer (see below):

# convert all factor to character
dat %>% mutate(across(where(is.factor), as.character))

# apply function (change encoding) to all character columns 
dat %>% mutate(across(where(is.character), 
               function(x){iconv(x, to = "ASCII//TRANSLIT")}))

# subsitute all NA in numeric columns
dat %>% mutate(across(where(is.numeric), function(x) tidyr::replace_na(x, 0)))

Original answer

Since Nick’s answer is deprecated by now and Rafael’s comment is really useful, I want to add this as an Answer. If you want to change all factor columns to character use mutate_if:

dat %>% mutate_if(is.factor, as.character)

Also other functions are allowed. I for instance used iconv to change the encoding of all character columns:

dat %>% mutate_if(is.character, function(x){iconv(x, to = "ASCII//TRANSLIT")})

or to substitute all NA by 0 in numeric columns:

dat %>% mutate_if(is.numeric, function(x){ifelse(is.na(x), 0, x)})